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Title Heavy Metal Contamination in Water and Sediment of To LichRiver in Inner City Hanoi( Dissertation_全文 )
Author(s) Nguyen Thi Thuong
Citation 京都大学
Issue Date 2013-09-24
URL https://doi.org/10.14989/doctor.k17881
Right 許諾条件により要旨・本文は2014-09-23に公開
Type Thesis or Dissertation
Textversion ETD
Kyoto University
Heavy Metal Contamination in Water and Sediment of To Lich River in Inner City Hanoi
Nguyen Thi Thuong
2013
ii
i
ACKNOWLEDGEMENTS
I would first and foremost like to express my deepest gratitude to my supervisor, Prof.
Minoru Yoneda, for his spending time and other resources on my PhD program and his
kindly comments on manuscripts of my published papers and on thesis manuscripts.
I am extremely grateful to Prof. Hiroaki Tanaka and Prof. Yoshihisa Shimizu, the
members of thesis committee, for providing key insights and critical feedback on my
work.
I gratefully acknowledge the financial support of Japanese Ministry of Education, Culture,
Sports, Science and Technology for my three years staying in Kyoto, Japan; Kyoto
University Human Security Engineering Program and Environmental Management
Leader Program, which partially funded my field work in Vietnam.
Many thanks to Dr. Ngo Trung Hai (Director, Vietnam Institute of Architecture, Urban
and Rural Planning), who allowed me to be away for three years, and my colleagues in
helping to do PhD degree.
I also would like to thank MPP Vu Duc A (Hanoi Environment and Natural Resources
Department) for his willingness to provide materials and share experience, and my best
friend Luu Hoa Binh (Hanoi Authority for Planning and Investment) for helping with data
collection. The same goes to the staffs from Institute of Environment Technology and
Hanoi Construction Verification and Laboratory Center for the co-operation during field
survey.
My best regards to past and present members at Lab of Environmental Risk Analysis,
Department of Environmental Engineering, Graduate School of Engineering, Kyoto
University, who proved to be very supportive and stimulating at various stages of my
study. Special thanks go to Ikegami san (for ICP-MS training and expertise), Nakamura
san, Takakura san and Pipie san (for helping in laboratory work), and Hoshihara san (for
generous help whenever needed).
I am much indebted to my family for their love, patience and constant support throughout
this endeavor. To all of you and to all those I did not mention, I say thanks for helping me
to get there.
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TABLE OF CONTENTS
Acknowledgements .............................................................................................................. i
Table of Contents ................................................................................................................ ii
Chapter 1: General Introduction ........................................................................................ 1
Chapter 2: Source Discrimination of Heavy Metals in Sediment and Water of To Lich
River in Hanoi City using Multivariate Statistical Approaches ........................................ 17
Chapter 3: An Assessment of Heavy Metal Pollution and Exchange between Water and
Sediment System in the To Lich River, Inner Hanoi City ................................................ 37
Chapter 4: Does Embankment Improve Quality of a River? A Case Study in To Lich
River Inner City Hanoi, with Special Reference to Heavy Metals ................................... 67
Chapter 5: General Discussion and Management Implications ....................................... 89
Chapter 6: Conclusions and Recommendations ............................................................. 101
1
CHAPTER 1. GENERAL INTRODUCTION
1.1. GENERAL CHARACTERISTICS OF HANOI CITY
Hanoi is capital city of Vietnam, located in Red river delta at 21°01′42″N and
105°51′12″E (Fig. 1.1). The city features a tropical monsoon climate with two distinct
seasons: Winter dry season (November to April) and summer rainy season (May to
October), which contains nearly 85% of total precipitation. The annual precipitation is
much changing year by year from 1200 to 2300 mm (Fig. 1.2). In rainy season especially
in July and August, there are some cases with rainfall up to 150 mm/day when storms
come. In contrast, dry season averages only 12 mm in December and January.
Hanoi was expanded in 2008 and currently covers a total area of 3,329 km2 with a
population of 6.7 million people in 2011. The inner Hanoi capital comprised ten districts,
namely Ba Dinh, Hoan Kiem, Dong Da, Hai Ba Trung, Tay Ho, Thanh Xuan, Cau Giay,
Hoang Mai, Ha Dong and Long Bien. In the past ten years, population in Hanoi increased
120,000 people annually, including many from in-migration. Average population density
is 2,013 people/km2, however in some inner districts like Dong Da and Hai Ba Trung, the
figure reached up more than 35,000 people/km2. Currently, population in inner city is 2.6
million people with annual growth rate of 3.8%, of which in-migration contributes
roughly 3%.
There are several rivers running through Hanoi region, namely Hong, Duong, Nhue rivers,
and To Lich River (TLR) system (Fig. 1.1). Among them, Nhue and TLR system are
responsible for receiving and conveying wastewaters for inner city Hanoi. TLR system
includes four main rivers with a total length of 38.9 km and covers a basin area of 77.5
km2. (1) TLR covers a basin of 20 km2 and has a length of 17 km, a width of 20 - 45 m,
and a depth of 2 - 4 m, starting from West lake in the North, receiving wastewaters from
western Hanoi then discharging to Nhue River in the South with maximum flow of 30
m3/s. (2) Kim Nguu River originates from central Hanoi and joins with TLR at Thanh
Liet. The river has a length of 11.9 km, a width of 25 - 30 m, and a depth of 2 - 4 m,
covering a basin area of 17.3 km2. Kim Nguu was embanked in 2002 and resulted in a
maximum flow of 15 m3/s. (3) Set River starts from central south Hanoi with a length of
6.8 km, a width of 3 - 4 m, and a depth 1.5 - 2.5 m, covering an area of 7.1 km2. The river
has maximum flow of 8 m3/s. Water from Set River is discharged to upstream of Kim
Nguu River. (4) Lu River also starts from central south of Hanoi with a length of 6,7 km,
a width of 7 - 10 m, and a depth of 2 - 3 m, covering a basin of 10.2 km2. The river has a
2
maximum flow of 6 m3/s. Lu River discharges water to TLR at downstream before
confluence of Kim Nguu with TLR. Besides, there are approximately 25 small channels
with a width of 3 - 5 m, a depth of 1.5 - 2.5 m, and a total length of 18.1 km in inner
Hanoi city. In addition, Hanoi is known as “city of lakes” with a total of 518 large and
small ones (Fig. 1.1). Besides serving as recreations, these lakes also function as
receiving untreated wastewaters in inner Hanoi city leading to many environmental
problems.
Fig. 1.1 River system and lakes in Hanoi
To Lich River system is under high polluted condition as result of diversity of
wastewaters discharged from various sources such as industry, hospitals, households,
agriculture, etc. There are about 2 million permanent citizens living in inner city Hanoi
(GSO 2010) and seasonal citizens, generating domestic wastewater to TLR system an
estimated volume of more than 190,000 m3/day. Meanwhile, discharge from industries
3
ranges between 240,000 to 263,000 m3/day, occupying 53 - 58% of the total wastewater
from inner city. There are five industrial zones located in Hanoi including 99 large
manufacturing plants of all types of industries, which release wastewater to TLR system
(Table 1.1). In addition with 369 large and medium scale industries, there are 14,000
small industry and handicrafts located in Hanoi (HENRD 2002). Twenty nine hospitals
and many big health centers with more than 25,000 beds also discharge roughly 6,000 m3
wastewater per day to TLR system (HENDR 2009).
Figure 1.2 Average monthly rainfall during 2002-2011
To improve water flow rate and reduce stagnation, the embankment was carried out in
many reaches of all four rivers in TLR system. In addition, to reduce pollution impacts
from TLR system, which may lead to deteriorate water supply source for downstream
provinces of Nhue River, regulatory Thanh Liet Dam (TLD) was built nearly at the end of
TLR and Yen So pumping station was built in southeastern Hanoi (Fig. 1.1). Recently,
TLR system functions as: (1) TLD is open when water level in Nhue River is low, then
water from TLR drains naturally to Nhue River; (2) TLD is closed when water in Nhue
River runs higher than in TLR and/or TLR water is too polluted, which may affect water
quality of Nhue River. In case of closing dam, water from TLR flows into Yen So
regulating reservoir and is finally pumped to the Red river (Fig. 1). In fact, to reduce
pumping costs, even highly polluted water is still discharged to Nhue River leading to
degradation of water quality at the downstream. In general, Thanh Liet Dam is opened
more than 320 days annually.
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10 11 12
Rai
nfal
l (m
m)
Month
2011 20102009 20082007 20062005 20042003 2002
4
Table 1.1. List of manufacturing plants of five industrial zones in basin of To Lich River
system, Hanoi
Type of industry Thuong Dinh - Nguyen Trai
Minh Khai - Vinh Tuy
Truong Dinh - Duoi Ca
Van Dien -Phap Van
Cau Buou
Mechanical 14 13 3 8 3
Construction material
- 6 - 2 1
Food processing 1 3 6 - -
Textile 4 11 2 - -
Leather 3 1 - - -
Printing - 1 - - -
Paper 1 - - - -
Ceramic 2 - 1 - -
Chemical 2 - - 2 1
Others 3 3 1 1 -
Total 30 38 13 13 5
1.2. WASTEWATER AND SEDIMENT CHARACTERISTICS AND THEIR IMPACTS ON ENVIRONMENT,
HUMAN , AND ECOSYSTEM
The world is facing with problems related to the management of wastewaters. This is due
to industrialization, population increase, and urbanized societies (USEPA 1993;
McCasland et al. 2008). The wastewaters generated from domestic and industrial
activities constitute major sources of water pollution load. This is a great burden in terms
of wastewater management and can consequently lead to a point-source pollution
problem, which not only increases treatment cost considerably, but also introduces a wide
range of chemical pollutants and microbial contaminants to water bodies (USEPA 1993,
1996; Eikelboom and Draaijer 1999; Amir et al. 2004).
The level of treatment ranges from no treatment to very sophisticated and thorough
treatments. Wastewaters are discharged to a wide variety of receiving environments: lakes,
ponds, streams, rivers, estuaries, and oceans. Wastewaters do contain pollutants of
concern since even advanced treatment systems are unable to remove all pollutants and
chemicals. Several environmental and health impacts resulted from insufficient
wastewater treatment have been identified in the scientific literature (Musmeci et al 2009;
Saracci and Vineis 2007; Pruss-Ustun and Corvalan 2007, 2006; Rothman and Greenland
1998; Suser 1991; and many others) and actions need to be taken to reduce these impacts.
5
The impacts, that wastewaters may have on water quality, plant and animal life, human
health, and beneficial water uses, include:
• decaying organic matter and debris can use up the dissolved oxygen in water
bodies, affecting life of aquatic biota;
• excessive nutrients, such as phosphorus and nitrogen, can cause receiving waters
over-fertilization, which can be toxic to aquatic organisms, reduce availability of
oxygen, alter habitat, and lead to a decline in species and/or population;
• chlorine compounds and inorganic chloramines can be toxic to aquatic
invertebrates, algae, etc.;
• bacteria, viruses, and disease-causing pathogens can pollute playground near
water bodies, leading to human waterborne diseases and restrictions on recreation;
• heavy metals, such as mercury, lead, cadmium, chromium, arsenic, etc., can have
acute and chronic toxic effects on species.
The process of collection and treatment of wastewaters also results in the release of
certain volatile chemicals into the air. The chemicals typically released in the large
volume include; methane, carbon dioxide, oxides of nitrogen and hydrogen sulfide, and
various other chemicals can be released to a smaller extent.
The physic-chemical characteristics of wastewaters of special concern are pH, dissolved
oxygen, oxygen demand (chemical and biological), solids (suspended and dissolved),
nitrogen (nitrite, nitrate and ammonia), phosphate, and heavy metals (DeCicco 1979;
Larsdotter 2006).
The pH is an important quality parameter of wastewaters. It is used to describe the acid or
base properties of wastewaters. pH values less than 5 and greater than 10 indicate the
presence of industrial wastewater and are non-compatible with biological operations. The
pH range of 6 - 9 is usually in the existence of biological life (USEPA 1996; Gray 2002).
Dissolved oxygen (DO) is another parameter in water requiring for the respiration of
aerobic microorganisms as well as all other aerobic life forms. The actual quantity of DO
is governed by the solubility, temperature, partial pressure of the atmosphere, and the
concentration of impurities such as salinity and suspended solids in the water (USEPA
1996; Metcalf and Eddy 2003). While, oxygen demand in the form of BOD or COD is the
6
amount of oxygen used by microorganisms as they feed upon the organic solids in
wastewaters (Water Environmental Federation 1996; Gray 2002; FAO 2007). In which,
the 5-day BOD is the most widely organic pollution parameter applied to wastewaters.
Wastewaters normally comprise 99.9% water and 0.1% of solids, in which discharges
from industrial and domestic sources respond high portion of those solids.
Phosphorus in water is essential constituents of living organisms. However, when
phosphorus input to water is higher than natural-balanced condition (Rybicki 1997), it
may lead to extensive algal growth (eutrophication). Controlling phosphorus discharge
from domestic and industrial wastewaters is a key factor in preventing eutrophication in
surface waters (Department of Natural Science 2006). Phosphate itself does not have
notable adverse effects on human health. On the other hand, nitrogen is important in
wastewater management and can have adverse effects on ecology and human, if
concentration is higher than 10 mg/L. Despite the fact that nitrates in some levels affect
infants, but do not pose any direct threat to older children and adults, it indicates the
presence of other serious residential or agricultural contaminants, such as bacteria and
pesticides (McCasland et al. 2008). Methemoglobinemia is the most significant health
problem associated with nitrate in water. Similarly, nitrogen in the form of ammonia is
toxic to fish and exerts an oxygen demand on receiving water by nitrifiers (CDC 2002).
Metals are of importance in water. The metals of importance in wastewater treatment are
As, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Mo, Ni, K, Se, Na, V, and Zn. Living
organisms require varying amounts of some metals (Ca, Co, Cr, Cu, Fe, K, Mg, Mn, Na,
Ni, and Zn) as nutrients for their proper growth. While, other metals (Ag, Al, Cd, Au, Pb,
As, and Hg) have no biological role and hence are non-essential (Metcalf and Eddy 2003;
Hussein et al. 2005). Heavy metals are one of the most persistent pollutants in
wastewaters. Unlike organic pollutants, they cannot be degraded, but accumulate
throughout the food chain, producing potential risks on human health and ecological
disturbances. Their over-presence in wastewaters is due to discharges from domestic,
industrial, vehicle emission, etc. The accumulation of heavy metals in wastewaters
depends on many local factors, such as the type of industries, way of life, and awareness
of their impacts on the environment through the careless disposal of wastes (Hussein et al.
2005; Silvia et al. 2006). The danger of heavy metal pollutants in wastewaters lies in two
aspects. First, heavy metals have the ability to persist in natural ecosystems for an
extended period. Secondly, they have the ability to accumulate in successive levels of the
biological food chain (Fuggle 1983). Although heavy metals are present in small
7
quantities in natural, it is almost exclusively through human activities that these levels are
increased to toxic levels in wastewaters (Nelson and Campbell 1991). Human can be
exposed to chemicals in wastewaters in various ways. They may ingest small amounts of
pollutants from consuming crops which are irrigated by wastewaters, aquaculture
products which live in polluted water body, and from absorbing contaminants through
their skin while contacting with wastewaters.
The major microorganisms found in wastewaters are viruses, bacteria, fungi, protozoa,
and helminthes. Although those microorganisms are criticized as a main source in
contributing to numerous waterborne diseases to human, they play many beneficial roles
in wastewater treatment as removing dissolved organic matter (Kris 2007), using in fixed
film systems, suspended film systems or lagoon systems in treatment plant to enhance
degradation of solids for less sludge production (Ward-Paige et al. 2005a). In addition,
wastewater microbes are also involved in nutrient recycling, such as phosphate, nitrogen,
and heavy metals. If nutrients that are trapped in dead materials are not broken down by
microbes, they will never become available to help sustain the life of other organisms.
Microorganisms are also responsible for the detoxification of acid mine drainage and
other toxins in wastewaters (Ward-Paige et al. 2005b).
The investigation of sediments from the water bodies is of great interest in aquatic
systems, since sediment quality is a good indicator of pollution in water column, where it
tends to accumulate the heavy metals and other organic pollutants, as well as provide
information on the impact of pollution sources. The potential environmental damage of
water bodies might be comparatively small if heavy metals are ultimately fixed in
sediments (Zoumis et al. 2001). Metal composition in the sediment may be controlled by
natural (e.g., mineralogy, weathering) and anthropogenic processes (Nesbitt 1979). The
chemical composition of the sediments can be used as a powerful tool to determine their
sources (Vital and Stattegger 2000). While, horizontal distribution of metals has provided
evidence that lateral variations in the chemical composition of surface sediments act as a
guide to local pollution centers (Förstner 1981).
A critical factor for sediment toxicity is contaminant bioavailability, the degree to which
contaminants can be taken up by plants and animals (Ankley et al. 1996). Sediment
parameters that affect heavy metal bioavailability include cation exchange capacity, total
organic carbon, Fe and Mn oxides, as well as the relationship between acid volatile
sulfides and simultaneously extracted metals.
8
Cation exchange capacity is based on the surface area of sediment grain particles
available for binding cations, such as hydrogen (H+) and free metal ions (e.g., Mn+2).
Sediments with a high percentage of small grains, such as silt and clay, have high surface-
to-volume ratios and can absorb more heavy metals than sediments composed of larger
grains. Total organic carbon is added to sediments primarily through the decomposition
of plant and animal matter, and domestic and industrial discharges. Organic carbon can
directly adsorb heavy metals from solutions applied to sediments (Liber et al. 1996).
However, it can also contain heavy metals accumulated by plants which is discharged and
decomposed in sediment (Peltier et al. 2003). Nonetheless, high percentages of small
grains in sediment are generally associated with reduced heavy metal bioavailability and
toxicity (Ankley et al. 1996).
The dominant geochemical processes responsible for the exchange of metals at the water-
sediment interface are adsorption and precipitation (Salomons and Forstner 1984; Wang et
al. 1997). Fe and Mn oxides and organic matter either as bulk phases or as coatings of
mineral particles are the main binders in sediments (Tessier et al. 1980). Binding fractions
of heavy metals in the sediments can be divided into five groups: exchangeable, carbonates,
hydroxides, organic and residuals. Both Fe and Mn can remove other heavy metals from
solution through oxidation, thus making them less bioavailable (Fan and Wang 2001). The
ways for doing this is by precipitating heavy metals from solution during oxide formation
(Simpson et al. 2000) and is direct adsorption onto preformed oxides (Dong et al. 2000).
Sulfide is known to interact with Fe under anaerobic conditions to form a solid, iron
sulfide (FeS). Other heavy metals such as Cu, Pb, Ni, Zn can be removed from solution by
displacing Fe and binding to the sulfide. This process has led to a relatively new parameter
for evaluating sediment toxicity, so called simultaneous extracted metal minus acid
volatile sulfide (SEM-AVS). The term AVS represents the amount of sulfide in sediments
available for binding heavy metals; SEM represents the amount of heavy metals in
sediment that could be available to plants and animals. If SEM exceeds AVS, the
sediments are potentially toxic (Di Toro et al. 1990; Hansen et al. 1996).
1.3. BENEFITS OF WASTEWATER REUSE IN AGRICULTURE AND ITS CONCERNED PROBLEMS
Sewage farm has been developed for more than 100 years in industrialized countries like
England, France, Germany and Australia, in which sewage was disposed to the farm for
natural treatment (now known as recycle and reuse), supporting water and nutrient in low cost
9
for farm. However, many of those farms were abandoned because of many environmental
problems, transmission of diseases, and contaminated products (Shevah 1999).
Municipal wastewater is less expensive and considered an attractive source for irrigation
in many countries, especially in arid and semi-arid countries. Advantages of reuse of
wastewaters in agriculture include: conserving water, cost-efficient method for domestic
wastewater disposal, reducing pollution of water bodies, reducing input costs for artificial
fertilizers, increasing crop yields, and providing a reliable water supply. However, it also
contains a number of important disadvantages (Bahri and Brissaud 1996; Weber et al.
1996) including: health risks to both irrigators who are in prolonged contact with
wastewaters and consumers of crops which are irrigated with wastewaters, contamination
of ground water especially with nitrates, buildup heavy metal pollutants in the soil, and
creation of habitat for disease vectors.
Since wastewater treatment technology has been improved, resulted in cost-effective
agriculture application. The reuse of treated wastewaters is receiving an increasing
attention as a reliable water resource. In many countries, treating wastewater for reuse is
important of water resources planning and implementation. This is aimed at releasing high
quality water supplies for potable use. Some countries, such as Jordan and Saudi Arabia
have national policies to reuse treated wastewaters. The general acceptance is using
wastewater in agriculture, justifying on agronomic and economic grounds, although care
must be taken to minimize adverse impacts on environment and human health (FAO 1992;
Metcalf and Eddy 2003; Rietveld et al. 2009; Sowers 2009). The option of reuse of
wastewater at least in agriculture is becoming necessary and possible as a result of climate
change, which leads to droughts and water scarcity, and the fact that discharge regulations
have been becoming stricter, leading to a better wastewater quality (Rietveld et al. 2009).
Management of irrigation with wastewaters should consider the nutrient content in
relation to the specific crop requirements and the concentrations of plant nutrients in the
soil, and other soil fertility parameters. In many areas of developing countries, untreated
wastewaters are used directly to small plots of vegetables and salad crops, which are
easily consumed raw as salad. The public health risks coming from this are obvious
(Mead and Griffin 1998; WHO 2004). However, such risks can be controlled by treating
wastewaters properly before irrigating crops, which minimize the transfer of pathogenic
and toxic contaminants into the agricultural products, soils, and surface and groundwater
(Batarseh et al. 1989). The nutrient supply from wastewaters to the soil is obvious such as
10
N, P, as well as organic matters (Sommers 1977; Pomares et al. 1984), but there is a
concern about the accumulation of potentially toxic elements such as Cd, Cu, Fe, Mn, Pb,
and Zn from both domestic and industrial discharges (Pescod, 1992). Nitrogen is much
available in wastewater especially from domestic source and is in forms of usability for
crops; organic nitrogen, ammonia, nitrate and nitrite, in which three later make up the
inorganic forms (Hurse and Connor 1999). Nitrogen in different forms is required by all
organisms for the basic processes of life to make proteins, grow and reproduce. Therefore,
wastewaters and its nutrients can provide significant benefits to the farming communities
and society in general.
1.4. AIMS OF THIS STUDY
In being urbanized societies like city Hanoi, wastewaters are dynamics in terms of both
quality and quantity. There are a number of responsible reasons; population increase
especially from in-migration and seasonal citizens, which is out of predictability leading
to uncertainty of amount and quality of their wastewaters, construction blooming, and a
number of industrial zones which were established in inner city for a long history. In
addition, wastewater treatment has not been much taken care, leading to serious
environmental problem especially for water bodies such as rivers, lakes and their
surrounding recreations. Monitoring and assessing pollution levels and quality of water
bodies for both water and sediment, and discriminating pollution sources should be
carried out periodically which will serve decision makers in issuing environmental
regulations to improve wastewater quality at sources before discharging to common
sewage system, and in planning wastewater treatment plant system, which collects all
wastewaters and treat them to suitable using purpose such as for irrigation.
The aims of the study are:
To discriminate sources of heavy metals in sediment and water of To Lich River using
multivariate statistical approaches.
To assess heavy metal pollution and exchange between water and sediment system in the
To Lich River, inner Hanoi City.
To evaluate the recovery of To Lich River after nine years embankment using river
quality index, with special reference to heavy metals.
11
1.5. OUTLINE OF DISSERTATION
CHAPTER 2 discriminates nature, anthropogenic, and/or mix sources of eight heavy
studied metals including Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb using hierarchical cluster
and principle component analyses. Meanwhile, enrichment factor and geo-accumulation
index were used to evaluate enrichment and contamination levels of heavy metals.
CHAPTER 3 assesses contamination levels of nine study sites, which corresponds to its
discharge sources as domestics, industrials, and/or mix. Besides using enrichment factor
and geo-accumulation index, quality guidelines including a threshold effect concentration,
a probable effect concentration (PEC), and mean PEC quotient were also used to evaluate
impacts that each site may pose to aquatic organisms. In addition, the current study area
was also compared to some polluted rivers around the world to understand the extent of
heavy metal pollution in To Lich River.
CHAPTER 4 evaluates current quality of To Lich River compared to that before
embankment nine years ago by using relative river quality index, with special reference to
quality of water and sediment through their heavy metal concentrations. The chapter also
includes estimation of total sediment currently accumulated in river bed and costs
required to treat those sediment to environmental friendly condition, estimation of heavy
metal and total organic carbon loads in each concerned river reach corresponding to its
discharged sources, and total load at the end of To Lich River which is discharged daily
to Nhue River in South Hanoi.
CHAPTER 5 presents general discussion and management implications for To Lich River
system basin.
CHAPTER 6 summarizes main findings in dissertation.
12
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17
CHAPTER 2. SOURCE DISCRIMINATION OF HEAVY METALS IN
SEDIMENT AND WATER OF TO LICH RIVER IN HANOI CITY USING
MULTIVARIATE STATISTICAL APPROACHES
Has been published in Environmental Monitoring and Assessment in press.
ABSTRACT
The concentrations of Cr, Mn, Fe, Ni, Cu, Zn, As, Cd and Pb were determined to evaluate
the level of contamination of To Lich River in Hanoi city. All metal concentrations in 0-
10 cm water samples, except Mn, were lower than the maximum permitted concentration
for irrigation water standard. Meanwhile, concentrations of As, Cd and Zn in 0-30 cm
sediments were likely to have adverse effects on agriculture and aquatic life. Sediment
pollution assessment was undertaken using Enrichment Factor and Geo-accumulation
Index (Igeo). The Igeo results indicated that sediment was not polluted with Cr, Mn, Fe
and Ni, and then pollution level increased in order of Cu < Pb < Zn < As < Cd.
Meanwhile, significant enrichment was shown for Cd, As, Zn, and Pb. Cluster and
principle component analyses suggest that As and Mn in sediment were derived from
both lithogenic and anthropogenic sources, while Cu, Pb, Zn, Cr, Cd, and Ni originated
from anthropogenic sources such as vehicular fumes for Pb and metallic discharge from
industrial sources and fertilizer application for other metals.
Keywords: Geochemical indices, Hanoi, Metals, Multivariate Statistical approaches,
Sediment.
18
2.1. INTRODUCTION
Trace elements, the so-called heavy metals, are one of the serious pollutants in natural
environment because of their persistence, toxicity, and bioaccumulation (Fang and Hong
1999; Tam and Wong 2000). Heavy metals tend to be trapped in the aquatic environment
and accumulate in sediment, which are probably released to the water through sediment
re-suspension, reduction-oxidation reactions, etc. Such processes enhance the dissolved
concentration of trace metals in water (Jones and Turki 1997; Wright and Mason 1999).
Since sediment acts as the carrier and the potential secondary source of contaminants in
river system (Calmano et al. 1990), the degree to which it becomes a source of pollution
depends on such factors as the proximity of contaminated sediments, river activity (e.g.
water flow rate) and the intensity of geomorphic activity of the river catchment (Martin
2000). Therefore, the analysis of river sediment is a useful method to study the metal
pollution in an area.
Heavy metals enter a river from a variety of sources; either natural or anthropogenic
(Adaikpoh et al. 2005; Akoto et al. 2008). The concentration of most of the metals in
unaffected rivers is very low, which is safe to biotic and is mostly derived from
weathering of rock and soil (Reza and Singh 2010). Meanwhile, the main anthropogenic
source of heavy metals to affected rivers, especially in inner cities, is from untreated
and/or partially treated disposals containing heavy metals from domestic and industrials
(Macklin et al. 2006; Nouri et al. 2008; Reza and Singh 2010). It is estimated that there is
in between of 30 and 98% of the total metal load accumulated in sediment-associated
forms (Gibbs 1973; Salomons and Förstner 1984). Sediment will become a potential non-
point source of pollution if it is deposited on the river banks or floodplain (Marcus 1989;
Martin 2000).
Hanoi, the capital of Vietnam, has witnessed the rapid economic growth and urban
expansion for recent decades, causing severe environmental pollution especially to inner
city river system. The domestic and industrial wastewater is untreated or partially treated
before discharging to To Lich River, the main drainage river in inner city of Hanoi,
resulting in serious deterioration of the water and sediment qualities, and related problems
as water-borne diseases. Previous investigations indicated that the concentration of heavy
metals in sediment of To Lich River was quite high because of the metallic wastewater
discharged from manufacturing plants located in catchment and longtime stagnation (Ho
and Egashira 2000; Nguyen et al. 2007; Kikuchi et al. 2009). It is said that heavy metal
19
concentrations in sediment and water in To Lich River exceeded the Vietnamese standard
for agriculture (Ho and Egashira 2000; Nguyen et al. 2007), even the contents in water
were not exceeding or only for several metals. It was reported that environment in Hanoi
city has been improved much in recent years as a result of treatment of industrial
wastewater from the enforcement of several environmental regulations. This paper aims
to evaluate the current status of heavy metal contamination in 0-10 cm water and 0-30 cm
sediment, and to discriminate the possible sources and enrichment of heavy metals in
sediment of To Lich River.
2.2. MATERIALS AND METHODS
2.2.1. Study area
The To Lich River has been a significant river throughout history of Hanoi city. The river
originates in the West Lake and flows through residential and industrial areas, before
joining the Kim Nguu River nearly at downstream, and finally enters Nhue River through
Thanh Liet Dam (Fig. 2.1). The dam was constructed to prevent contaminated water of
To Lich to Nhue. Its gate is almost closed in dry season and is manually controlled in
rainy season according to the water level of To Lich. Total length of To Lich is
approximately 17 km, covering a catchment of about 20 km2. A number of manufacturing
plants are located between S3 and S4 (Fig. 2.1), including a complex of factories of
mechanical engineering, rubber, soap, and tobacco in Thuong Dinh and Thanh Xuan
districts. Meanwhile, leather and paint factories are located near S1 and S6 (Fig. 2.1),
respectively. A plastic company is located upstream from confluence with Lu River
(Nguyen et al. 2007). The volume of sewage dumped into To Lich was approximately
290 thousand m3 per day, which accounted two-thirds of wastewater generated from inner
Hanoi city (Nguyen et al. 2007).
2.2.2. Sample collection
Surface water and sediment samples were taken from eight sites located along the river
(Fig. 2.1) in the dry season, March 2011. Polypropylene bottles were immersed 10 cm
deep below the water surface. Then, water samples were acidified with conc. HNO3 to pH
< 2, transported to the laboratory, and stored in a refrigerator until analysis. Sediment
samples, on the other hand, were taken at 0-30 cm from the river bed using a self-made
sediment sampler and placed in polyethylene bottles.
20
Fig. 2.1 Map of To Lich River catchment showing sampling sites
2.2.3 Chemical analysis
Collected sediments were air-dried and passed through 1-mm stainless steel sieve to
remove big particles. The samples were then heated in drying oven at 60oC until constant
weight and lightly powdered within an agate mortar for homogenization. A microwave
unit was used for the digestion of sediment samples with acid. Briefly, 50 mg dry
sediment was placed in a vessel and successively digested with 10 mL of conc. HNO3 in a
microwave digestion system (USEPA 2007). After cooling, the digest was adjusted to 50
mL volume with Mili-Q water and finally filtered through a membrane filter (0.45-µm
pore size). Concentration of heavy metals (Cr, Mn, Fe, Ni, Cu, Zn, As, Cd and Pb) in
acid-digested sediment and water samples was determined using ICP-MS.
21
2.2.4. Statistical analysis
Multivariate approaches were used in this study to assess the interrelationships among the
measured data, since they have been successfully used in geochemical and ecochemical
studies (Soares et al. 1999; Sakan et al. 2009; Li and Zhang 2010).
The Geo-accumulation Index (Igeo) introduced by Müller (1981) was employed to assess
the heavy metal contamination in sediment by comparing current concentrations with pre-
industrial levels. Values of Igeo were calculated by the following formula (Eq. 2.1):
Igeo = Log2Cn
1.5Bn (2.1)
where Cn is the concentration of metal n examined in the sediment and Bn is the
geochemical background concentration of the metal n. Factor 1.5 is used because of
possible variations in background values due to lithogenic effects. As the background
value of the concerned metals in current study site is not available, the earth crust values
(Turekian and Wedepohl 1961) were adopted. The values of Igeo were classified into
seven classes (Müller 1981; Bhuiyan et al. 2010); Igeo≤0 (Class 0: practically
uncontaminated), 0<Igeo≤1 (Class 1: uncontaminated to moderately contaminated),
1<Igeo≤2 (Class 2, moderately contaminated), 2<Igeo≤3 (Class 3, moderately to heavily
contaminated), 3<Igeo≤4 (Class 4, heavily contaminated), 4<Igeo≤5 (Class 5, heavily to
extremely contaminated), 5>Igeo (Class 6, extremely contaminated). Class 6 reflects 64-
fold enrichment over the background value (Singh et al. 1997).
Enrichment Factor (EF) was used to determine whether metals in sediment were of
anthropogenic origin (Simex and Helz 1981). To identify anomalous metal concentration,
geochemical normalization of the heavy metal data to a conservative element, such as Al,
Fe, and Si was employed. Several authors have successfully used iron to normalize heavy
metal contaminant (Schiff and Weisberg 1999; Mucha et al. 2003, Seshan et al. 2010;
Varol and Sen 2012). In this study, iron was also selected as a main conservative tracer
(while, Mn was also selected for comparison) to discriminate natural from anthropogenic
components. The EF of each concerned metal was expressed by the following equation
(Eq. 2.2):
EF = (��� ��)sample⁄(��� ��)background⁄ (2.2)
22
where (Metal/Fe)sample is the metal to Fe ratio in the sample of interest; (Metal/Fe)background
is the natural background value of the metal to Fe ratio. The choice of background values
plays an important role in the interpretation of geochemical data, in which several authors
(Loska and Wiechula 2003; Olivares-Rieumont et al. 2005; Singh et al. 2005; Pekey
2006b) have successfully used the average shale values or the average crustal abundance
data as reference baselines. The background values for EF calculation were similar as
those used in the aforementioned Geo-accumulation Index calculation. Value of
enrichment factor < 1 indicates no enrichment, 1-3 is minor, 3-5 is moderate, 5-10 is
moderately severe, 10-25 is severe, 25-50 is very severe, and > 50 is extremely severe
enrichment (Sakan et al. 2009).
Hierarchical clustering analysis is undertaken according to the Ward method (Ward 1963)
with Pearson distances (Zhou 2008). Ward method was considered superior in the aspects
of giving a larger amount of correct classified observations in comparison with other
methods (Sharma 1996). Results are shown in a dendrogram where steps in the
hierarchical clustering solution and values of the distance between clusters are
represented.
Principal component analysis (PCA) has been widely used to identify possible sources of
heavy metals in sediments; natural, anthropogenic or mixed (Facchinelli et al. 2001; Micó
et al. 2006). PCA reassembles the original variables into several integrated groups
unrelated to each other and selects less comprehensive variables from the integrated
groups to reflect the original variables according to the actual needs. The result of PCA
indicates that heavy metal concentrations can be reduced to several components, which
represent all the heavy metals in samples.
2.3. RESULTS AND DISCUSSION
2.3.1. Heavy metal contamination
The statistical summary for heavy metal values in 0-30 cm sediment samples is given in
Table 2.1. The concentration distribution of metals follows the decreasing order: Fe > Mn
> Zn > Cr > Cu > As > Pb > Ni > Cd. Based on mean values, Fe (35,092.3 mg/kg) was
the dominant metal in the sediment samples, followed by Mn (519.1) and Zn (477.9),
while Cd showed the minimum mean (4.4 mg/kg) in the sediment samples. High standard
deviation was found for Fe (46,087.0) and As (169.1) as a result of high concentration of
these two metals in S7, located right before Thanh Liet Dam (Fig. 2.1). The dam
23
closing/opening regime resulted in stagnation of water and sediment there in dry season,
when samples were collected. The values of the Geo-accumulation Index (Table 2.1)
were observed to be negative for Mn (-1.3), Fe (-1.0), Ni (-0.7) and Cr (-0.3), suggested
that the sediment was not polluted by such four metals. Meanwhile, it was slightly
polluted with Cu (0.4), and moderately with Pb (1.2) and Zn (1.8). The sediment was
under of moderate to strong pollution with As due to high value of Igeo (2.1). Especially,
the highest Igeo value of Cd (3.3) suggested the sediment was at strong pollution by this
metal. In summary, the Igeo values of the nine heavy metals in sediment decreased in the
order of Cd > As > Zn > Pb > Cu > Cr > Ni > Fe > Mn. By using Fe as normalizing
element, Enrichment Factor (EF) indicated the similar order of metal pollution degrees as
Igeo (Table 2.1). There were no enrichment of Mn (0.8) and Ni (1.3), minor enrichment for
Cr (1.6) and Cu (2.62), while Pb (4.5) was at moderate enrichment level. Zn (6.8) and As
(8.7) values fall within 5 and 10 suggesting the sediment was moderately severe enriched
by those two metals. Amazingly, the EF value of Cd shot up to 19.9 indicating the severe
enrichment of this metal in sediment. Even using Fe or Mn as normalizing element, the
order and degree of enrichment (Sakan et al. 2009) for concerned metals in sediment were
almost similar (Table 2.1). This indicated that beside using Fe, Si and Al, Mn can also be
used as normalizing element in evaluating metal enrichment degree, especially for
polluted urban rivers such as To Lich in Hanoi city.
Table 2.1. Heavy metal concentration (mg/kg) in 0-30 cm sediment, Enrichment Factor
(EF), and Geo-accumulation Index (Igeo)
Heavy metal Mn Fe Ni Cr Cu Pb Zn As Cd
Min 311.1 15,323.5 23.9 77.1 35.1 33.2 305.2 19.3 0.8
Max 912.7 148,912.1 111.4 174.0 155.9 90.5 718.1 501.8 11.8
Mean 519.1 35,092.3 64.8 107.9 87.7 67.1 477.9 83.9 4.4
Standard deviation
182.9 46,087.0 27.9 29.8 40.1 19.8 145.4 169.1 4.3
Average shale1
850 47,200 68 90 45 20 95 13 0.3
Igeo -1.3 -1.0 -0.7 -0.3 0.4 1.2 1.8 2.1 3.3
EF2 0.8 1.0 1.3 1.6 2.6 4.5 6.8 8.7 19.9 EF3 1.0 1.0 1.6 2.1 3.4 5.7 9.2 7.8 23.5
1 World geochemical background value in average shale (Turekian and Wedepohl 1961). 2 using Fe as normalizing element. 3 using Mn as normalizing element.
24
In comparison with the sediment quality guidelines (SQGs), the concentrations of Zn and
Cd (Table 2.2) were exceeding the maximum permissible concentrations for crops (Steve
1994). There are several pumping stations located along To Lich River, which may also
pump sediment for enrichment agricultural field, negatively affecting on quality of
agricultural products. It is also important to determine whether the concentration of heavy
metals in sediment in this study poses a threat to aquatic life, since water of To Lich River
is still used for aquaculture after discharging to Nhue River. The heavy metal
concentrations found were compared with consensus-based threshold effect concentration
(TEC) and probable effect concentration (PEC) values (MacDonald et al. 2000; Table
2.2). Mean values of Ni, Zn, and As exceeded the PEC, which likely result in adverse
effects on aquatic life. Considering maximum concentrations (Table 2.1), values of six of
seven concerned metals much exceeded (Table 2.2). These suggest that sediment from To
Lich River is not suitable for both crops and aquaculture.
Table 2.2. Comparison of heavy metal concentration (mg/kg) in study area with sediment
quality guidelines
Heavy metal Cr Mn Fe Ni Cu Zn As Cd Pb
This study 107.9 519.1 35,092.3 64.8 87.7 477.9 83.9 4.4 67.1
SQG-unpolluted1 < 25 na na < 20 < 25 < 90 < 3 na < 40
SQG-moderately polluted1
25-75 na na 20-50 25-50 90-200 3-8 na 40-60
SQG-heavily polluted1
> 5 na na > 50 > 50 > 200 > 8 > 6 > 60
MPC2 400 na na 110 200 450 - 3 300
TEC3 43.4 na na 22.7 31.6 121.0 9.8 0.9 35.8
PEC4 111.0 na na 48.6 149.0 459.0 33.0 4.9 128.0
1 USEPA sediment quality guidelines (Pekey 2006a). 2 Maximum permissible concentrations of potentially toxic heavy metal for crops (Steve 1994). 3 Threshold effect concentration, 4 Probable effect concentration (MacDonald et al. 2000). na data not available.
Table 2.3 summarizes the statistical data set of 0-10 cm water samples. The metal
concentrations in water from To Lich River followed the order: Mn > Zn > As > Pb > Ni
> Cu > Cr > Cd, which was dissimilar to that in sediment (Table 2.1). This indicated the
distinct in the balance of heavy metals in aquatic and sedimentary systems (Varol and Sen,
2012). The speed of stagnation and dissolve of heavy metals were different depending
25
much on water flow rate, metal concentrations, etc. (Marcus 1989; Martin 2000), which
led to differences in concentration order of heavy metal in sediment and water. The
highest metal concentration in water belonged to Mn (216.2 µg/L), followed by Zn (51.1),
As (39.1), other metals (Pb, Ni, Cu, and Cr) with mean concentration of lower than
10µg/L. Cd was observed to have lowest concentration in the water samples with
maximum value of 0.2 µg/L. Comparing to previous data (Table 2.3; CENMA 2008;
Kikuchi 2009) on heavy metal contamination in water, concentration of Ni, Zn, As, and
Pb tended to increase while that of Cr, Mn, and Cu decreased. This suggested that
environment of To Lich River has been either not yet improved or improved not such
much even several regulations on environment protection were issued recently.
Table 2.3. Heavy metal concentrations (µg/L) in water and mean concentration reported
from previous studies
Heavy metal Cr Mn Ni Cu Zn As Cd Pb
Min 2.0 83.7 5.0 3.0 28.0 13.1 na 6.0
Max 5.0 400.8 13.0 7.0 93.0 76.2 0.2 11.0
Mean 2.9 216.2 7.6 4.5 51.1 39.1 na 8.1
Standard deviation 1.4 87.1 2.6 1.7 20.2 18.1 na 1.6
Sample collected in rainy season 20081
< 5.0 230.4 na na na 14.7 na < 0.1
Sample collected in June 20062
11.2 116.0 3.4 8.4 36.1 10.3 na 2.8
Sample collected in October 20052
8.4 114.0 6.0 4.6 31.6 5.6 na 1.9
1 CENMA (2008). 2 Kikuchi et al. (2009). na data not available.
Among eight concerned heavy metals in water (Table 2.4), Mn had the concentration
exceeded the WHO (2006) maximum permitted level for irrigation water standard, even
though it has been widely used for agriculture irrigation. Water of To Lich River has not
been directly used for aquatic life, however after discharging to Nhue River it is used for
aquaculture. Concentration of Ni, Cu, Zn, As, and Cd in water was still lower than
permitted level for aquatic life (USEPA 2006).
26
Table 2.4. Comparison of heavy metal concentration (µg/L) in study area with water
quality guidelines
Heavy metal Cr Mn Ni Cu Zn As Cd Pb
This study 2.9 216.2 7.6 4.5 51.1 39.1 na 8.1
WHO1 100 200 200 200 2,000 100 10 5,000
USEPA2 na na 470 13 120 340 2 na
1 Irrigation water standard (WHO 2006). 2 Acute values for protection of freshwater aquatic life (USEPA 2006). na data not available.
2.3.2. Hierarchical cluster analysis
Cluster analysis (CA) was performed to identify relationships among metals and their
possible sources (Casado-Martinez et al. 2009; Chung et al. 2011). Four clusters were
observed (Fig. 2.2) for the metals in 0-30 cm sediment with significant linkage distance,
indicating relatively high independency for each cluster. The first cluster was formed by
As and Mn, which were derived from a mix of anthropogenic and lithogenic sources. Mn
and As were extremely well correlated with each other presented by high correlation (r =
0.99; Table 2.5). Mn is found abundant in the Earth’s crust (Turekian and Wedepohl
1961), however its concentration was higher at downstream site (S7; Fig. 2.1) after a
complex of manufacturing plants. Therefore, Mn can be from both natural and
anthropogenic sources. As, the redox sensitive element, is commonly more soluble in
oxidized groundwater occurring as oxyanion or in the form of AsO42- or H2AsO4
- (Chen
et al. 2007). However, in reducing waters, As tends to be incorporated in insoluble
minerals (Welch et al. 1998). Cluster 2 contained Cd and Ni, which were moderately
correlated (r = 0.57). These two metals were mainly derived from anthropogenic sources
(e.g. inorganic fertilizer application, mechanical engineering). Cluster 3 containing Cr and
Pb, and cluster 4 containing Cu and Zn were derived from anthropogenic sources (e.g.
vehicle fumes, leather manufacture), which were also confirmed by relatively strong
correlations (Table 2.5). The order of significance of clusters was following: Cluster 1 >
Cluster 4 > Cluster 3 > Cluster 2 (Fig. 2.2).
27
Fig. 2.3 illustrates the dendrogram of metals in water samples with three main clusters.
The strong correlation between Cr and Zn (r = 0.75) was observed in the second cluster.
Cu and Ni (r = 0.60), which well correlated with each other, were associated with Pb to
form the first cluster. The third cluster was formed by As and Mn (r = 0.51). The inter-
element correlations in each cluster were relatively weaker than that in sediment,
representing by linkage distances in Fig. 2.2 and Fig. 2.3. The elements grouped in each
cluster in water and that in sediment were also different, except correlated pair formed by
As and Mn. Long history of sedimentation (Martin 2000), the difference of amount and
component of wastewater discharged to To Lich River by years, seasons and
manufacture’s working schedules, water flow rate, and opening regime of Thanh Liet
Dam (Fig. 2.1) responded for the such differences.
Linkage distance (Pearson)
Fig. 2.2 Dendrogram of specified metals in 0-30 cm sediment using Ward’s method
28
Table 2.5. Statistical results of factor analysis for 0-30 cm sediment
Matrix to be factored
Cr Mn Ni Cu Zn As Cd Pb
Cr 1
Mn 0.03 1
Ni 0.12 0.47 1
Cu 0.49 0.04 0.37 1
Zn 0.27 -0.37 0.09 0.79 1
As -0.17 0.85 0.09 -0.25 -0.48 1
Cd 0.08 0.22 0.57 -0.10 -0.27 -0.19 1
Pb 0.62 0.59 0.41 0.70 0.21 0.36 -0.03 1
Rotated loading matrix (VARIMAX Gamma=1.000)
PC1 PC2 PC3
Cu 0.961 -0.08 0.05
Pb 0.781 0.572 0.10
Zn 0.751 -0.46 -0.18
Cr 0.692 0.01 0.11
As -0.18 0.961 -0.15
Mn 0.07 0.931 0.29
Cd -0.15 -0.07 0.951
Ni 0.33 0.23 0.801
Eigenvalues 2.72 2.39 1.70
% total variance
33.96 29.92 21.20
Cumulative % 33.96 63.88 85.08
Values in bold are statistically significant at p < 0.05. 1 Strong positive loadings (values > 0.7), 2 Moderate positive loading (0.5 < values < 0.7).
29
Linkage distance (Pearson)
Fig. 2.3 Dendrogram of specified metals in 0-10 water using Ward’s method
2.3.3. Principal component analysis
Principal component (PC) analysis is applied to quantitatively evaluate the clustering
behavior with Varimax normalization. According to Cattell and Jaspers (1967), PCs with
eigenvalue > 1 were retained. The results for heavy metal contents in 0-30 cm sediment
are given in Table 2.5 and Fig. 2.4. Three factors were originated with a cumulative
variance of 85%. The first factor (PC1) contributed 34% of total variance, showing strong
positive loadings on Cu (0.96), Pb (0.78) and Zn (0.75), and moderate positive loadings
on Cr (0.69; Table 2.5). This association may be attributed to local industrial effluents. Cu
may result from mechanical engineering and Cu-based agrochemicals/ phosphate
fertilizers, which was presented by cluster of Cu and Zn (Fig. 2.2). Zn and its compounds
have been used in different manufactured goods (e.g. paint, rubber/automobile tires) and
in fertilizers applied in agriculture in river catchment. Chromium salt may be used in
leather processing, which is located near S1 (Fig. 2.1), thus the effluents may contain high
levels of Cr. Meanwhile, paint industry located near S6 (Fig. 2.1) could also be
considered as one of pollution sources. The second factor (PC2) accounted for 30% of the
total variance and contained As (0.96), Mn (0.93) and Pb (0.57; Table 2.5); thus covering
metals originated from both natural and anthropogenic sources. The occurrence of Mn
may be due to its common presence in the basic rock, since the concentration of this
element was lower than background values (Igeo < 0; Table 2.1). As is well correlated with
Mn (r = 0.85) as shown in correlation matrix (Table 2.5) and cluster analysis (Fig. 2.2),
suggesting that As may originate from parent materials as well. In addition, As also
0 2 31
Pb
Cu
Ni
Cr
Zn
As
Mn
Cluster 1
Cluster 2
Cluster 3
30
originates from anthropogenic source, since arsenate and arsenite are utilized in
production of dye stuffs and a preservative of leather products (Japan Environmental
Sanitation Center 2005). Meanwhile, the presence of Pb in PC2 may suggest a source of
vehicular fumes, since before 2007 gasoline blended with lead was widely used in
Vietnam (Fig. 2.4). The third factor (PC3), explaining 21% of total variance, contained a
high loading on Cd (0.95) and Ni (0.80), which had their origin mainly in industrial
sources. This corresponded to cluster 2 (Fig. 2.2). As mentioned previously, using
phosphate fertilizers was an important source of heavy metals to To Lich River sediment
including Cd. Other sources of Cd may include other inorganic fertilizers (e.g. nitrogen or
potash), atmospheric deposition or anthropic wastes such as sewage sludge, wastewater or
waste materials. Ni originated from mechanical engineering, since it is an alloying metal.
It may also come from untreated wastewater from nearby. In general, the results of
principal component analysis (Table 2.5) have shown to be coincided with cluster
analysis (Fig. 2.2) for 0-30 cm sediment.
Fig. 2.4 Loading plots of principal component analysis for the three rotated components
31
For water data set, three factors were observed with a cumulative variance of 80%. PC1
was responsible for 31% variance and is best represented by Cu, Pb, and Ni with loadings
of 0.90, 0.83 and 0.77, respectively. PC2 contained Zn (0.94) and Cr (0.92), accounting
for 27% variance. The metals belonged to PC1 and PC2 mainly derived from anthropic
wastes discharged into river. Meanwhile, As (-0.94) and Mn (-0.76) showed strong
negative loadings in PC3 with total variance of 22%.
2.4. CONCLUSIONS
Heavy metal assessment and source discrimination are important for environmental
improvement and protection strategy, especially for urbanizing cities as Hanoi, Vietnam.
To Lich is one of the four main rivers, discharging three fourth wastewater in inner Hanoi
city. The water of this river is not suitable for irrigation since Mn concentration was
exceeding permitted concentration standard, while concentrations of As, Cd and Zn in
sediment were likely to have adverse effects on agriculture and aquatic life. It is
concluded that environment of To Lich River has not yet been improved even several
regulations on environmental protection had been issued recently.
Principal component analysis indicated that As and Mn originated from both
anthropogenic and natural sources, while Cu, Cr, Cd, Ni and Zn were mainly from local
industrial influence, and Pb was from vehicular fumes. However, the ratio of source of
heavy metals (e.g. mechanical engineering, rubber, soap, leather, hospital), which may
support local government in issuing suitable environmental protection regulations and
countermeasures, was not covered in this studied.
32
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37
CHAPTER 3. AN ASSESSMENT OF HEAVY METAL POLLUTION AND
EXCHANGE BETWEEN WATER AND SEDIMENT SYSTEM IN THE TO LICH
RIVER, INNER HANOI CITY
Has been under review by CATENA.
ABSTRACT
The To Lich River (TLR) serves as a main receptor of wastewater from Hanoi inner city
and supplying irrigation water for downstream areas. With the urbanization in recent
decades, untreated and/or partially treated wastewater from both industry and household
has been discharged to river leading to serious environmental problems. Heavy metal
concentrations in surface water and different sediment layers at nine sampling positions
along TLR were analyzed. Enrichment factor, Geo-accumulation index (GI), cluster
analysis, and quality guidelines were used to assess current status and possible risks that
may arise from heavy metal contamination. Mn concentration in surface water exceeded
the irrigation water limit at seven of nine sites. Meanwhile, Cd was the most
contaminated metal causing heavy sediment
Keywords: Cluster analysis, Geochemical indices, Metal accumulation, Quality
guidelines, Sediment
38
3.1. INTRODUCTION
Heavy metal contamination in environment is of major concern because of their toxicity
and threat to human life and the environment (Purves 1985).The majority of chemicals
discharged into river system eventually end up in sediments that may act as a sink as well
as a source of pollution (Beg and Ali 2008). Vegetables irrigated with heavy metal
contaminated water increase heavy metal accumulation in their edible portions (Butt et al.
2005; Sharma et al. 2007; Kiziloglu et al. 2008). In addition, heavy metal contaminated
sediments have negative effects on root and shoot growth of crops (Beg and Ali 2008).
Disposal of dredged contaminated sediments may affect the surrounding environment due
to the presence of harmful organic compounds and trace metals (Singh et al. 2000).
Meanwhile, long-term leaching and migration of contaminants from improperly disposed
sediment as on river banks and floodplain can result in contamination of both surface and
ground water (Maskell and Thornton 1998). Therefore, sediment quality is an important
focus in the assessment, protection, and management of aquatic ecosystems. Because it
affects the fate of many chemicals, which are potential impacts on organisms exposed to
sediments with elevated chemical concentrations (Smith et al. 1996).
It is frequently said that humic substances play a major role in controlling the behavior
and mobility of metals in sediment, that are essential trace elements or pollution-derived
heavy metals (Livens 1991). Organic matter exists as dissolved and suspended forms,
and/or in the bottom sediments. Those forms of the organic matter interact with heavy
metals (Mulligan and Yong 2006). Sediments containing high amounts of organic matter
tend to accumulate higher metal levels (Facetti et al. 1998; Nguyen et al. 2010), because
their compounds have pronounced metal binding properties (Bolt and Bruggenwert 1976).
Heavy metal concentrations tended to decrease with the increase of sediment depth,
meanwhile Pb, Zn, and Cr contents tended to increase toward downstream distance
(Subramanian et al. 1987).
Several studies (Ho and Egashira 2000; Nguyen et al. 2008, 2010) on quality of river
water and sediment in inner city of Hanoi indicated that heavy metal concentration
exceeded the maximum permissible concentrations for agriculture. However, that in water
of To Lich River (TLR) was lower than Vietnamese surface water standard (Kikuchi et al.
2009). Those indicate the complexity of heavy metal contamination in TLR. The fact that
resources of TLR are still being used for agriculture and there is a dense population living
near river bank, which became playground. Regular study on contamination degree of
39
water and sediment is needed to direct the use of resources and a proper management
scheme for TLR basin. Thus, the aims of this work are (1) to determine heavy metal
concentration and distribution in water and sediment of the TLR and (2) to assess degree
and extent of metal contamination in the river using statistical approaches and quality
guidelines.
3.2. MATERIALS AND METHODS
3.2.1. Description of study area
The To Lich River (TLR) is one of four main rivers in inner city of Hanoi; those rivers
receive and discharge 451,000 m3 water/day including industrial, household, and hospital
wastewaters (Nguyen 2005). TLR starts from West Lake in North Hanoi, running through
residential areas in upstream and industrial area in downstream before discharging to
Nhue River in South Hanoi (Fig. 3.1). The River has a length of approximate 17 km and
covers a basin area of 20 km2. The first 3.1 km from upstream of TLR (between sampling
position 1 and 2 in Fig. 3.1) has not been embanked, while the embankment at
downstream was finished in 2002 except the section between sampling position 6 and 7
(Fig. 3.1) because of difficulty in land clearance. As a result of embankment, the river has
a width of 20-45 m, depth of 2-4 m, and maximum flow capacity of 30 m3/s. There are
239 point sources, including pipe culverts sized from 300 to 1,800 mm in diameter and
box culverts sized from 1,200 x 1,200 mm to 3,300 x 3,300 mm, discharging wastewater
to TLR (Nguyen 2005). Non-point sources are also available, which is the illegal
dumping of domestic and construction waste on river bank or directly to river.
Wastewater discharged to TLR amounts 290,000 m3/day, accounted for 64% of total
wastewater in the city. Sixty percent of 290,000 m3 generated from industry, 2,000 m3
was from hospitals, and the remaining amount was household wastewater (HENRD 2003).
In dry season, water discharged from West Lake is limited because of low water level;
most water in TLR is wastewater from households and industry with low flow rate and
high pollution (HENRD 2009).
There are 33 manufacturing plants discharging wastewater to TLR without appropriate
treatment (EIO 2001), except 4.4% (Nguyen 2005). Thirty of those plants are from
Thuong Dinh - Nguyen Trai Industrial Zone, which discharge wastewater to 9-16 km
downstream section of the river; including 14 enterprises of mechanical industry, four of
textile industry, three of leather industry, two of chemical industry (rubber and soap), two
40
of ceramic industry, one of food processing industry (tobacco), one of paper industry, and
three other enterprises.
Fig. 3.1 The sites of sampling position
At 0.5 km from downstream (Fig. 3.1), Thanh Liet Dam, which has maximum water level
of 4.5 m and discharge capacity of 45 m3/s, was built to control water flow direction of
TLR. In general, when water level of Nhue River is lower than that of TLR the dam is
open. Conversely the dam is closed, when water of TLR is in low level and/or too
polluted it may affect the aquaculture in downstream of Nhue River. In such case, water
runs to Yen So Lake through Kim Nguu River (Fig. 3.1) and then it is pumped to Hong
River.
41
3.2.2. Sample collection
Water (at 10 cm depth) and sediment of different depths (0-30, 30-60, 60-90, and 90-120
cm) were collected at nine positions along the river (Fig. 3.1). The distances from
upstream to sampling positions are shown in Table 3.1. The first sampling position was
located at 0.2 km from West Lake in un-embankment section. Sampling positions 2, 3,
and 4 were at embanked section, mostly receiving household and hospital wastewaters.
The remaining sampling positions receive various types of wastewater including
industrial effluents. Position 5 was located at intersection, where Lu River discharges to
TLR, meanwhile positions 6 and 7 were at the un-embankment section of TLR. Position 8
was located at intersection between Kim Nguu River and TLR, and position 9 was located
below Thanh Liet Dam at 0.4 km from downstream (Fig. 3.1). All samples were collected
in dry season in March 4-5, 2011.
Water samples were collected in polypropylene bottles and stored at 4oC in refrigerator
until analysis. For heavy metal determination, the water samples were acidified with conc.
HNO3 to pH < 2 (1.5 ml conc. HNO3 per liter of sample). The pH of water was measured
in situ using a portable pH meter. Sediment samples, on the other hand, were taken from
river bed using a self-made sediment sampler and put into polyethylene bottles.
3.2.3. Chemical analysis
Total organic carbon (TOC) contents in water and sediment were analyzed using a TOC
analyzer (TOC-5000A, Shimadzu). For heavy metal analysis, sediment samples were air-
dried at room temperature and passed through 1mm stainless steel sieve to remove big
particles. Then the samples were heated in an oven at 60oC until constant weight,
powdered and homogenized. As for microwave-assisted acid digestion procedure,
approximately 50 mg dry homogenized sediment was placed in a vessel and successively
digested with 10 mL of conc. HNO3 in a microwave digestion system (USEPA 2007).
After cooling, the digest was transferred into a plastic volumetric flask and adjusted to 50
mL volume with Mili-Q water. The sample was finally filtered through a membrane filter
(0.45 µm pore size). Metal concentrations (Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, and Pb) in
water and acid-digested sediment samples were determined using ICP-MS.
Standard operating procedures, calibration with standards, and analysis of reagent blanks,
and analysis of replicates were used to guarantee the quality of analytical data. Analysis
for all samples was carried out in triplicate to get the mean as final data.
42
3.2.4. Sediment contamination assessment
3.2.4.1. Enrichment factor
Enrichment factor (EF) was calculated using the following equation (Eq. 3.1):
(3.1) (Metal/Fe)
(Metal/Fe)EF
background
sample=
in which, (Metal/Fe)sample is the ratio of metal to Fe in the sediment samples and
(Metal/Fe)background is the ratio of natural background value of the corresponding metal to
Fe. As background values of the metals of concern in current study site are not available,
the earth crust values (Turekian et al. 1961) were used (Singh et al. 2005).
3.2.4.2. Geo-accumulation index
The calculation of Geo-accumulation index (GI) was following equation 3.2 (Eq. 3.2)
(3.2) 1.5B
CLogGI
n
n2=
where Cn is the concentration of metal n in sediment in this study and Bn is the
geochemical background concentration of the corresponding metal . The background
values were similar as those used in Enrichment factor calculation. Figure 1.5 is the
background matrix correction factor due to lithospheric effects (Memet and Bulent 2012).
3.2.4.3. Sediment quality comparison
The quality of sediment of each sampling position was evaluated using the consensus-
based sediment-quality guidelines (SQGs), which assess possible risk to aquaculture from
the heavy metal contamination. Guidelines consist of a threshold effect concentration
(TEC) below which adverse effects are not expected to occur and a probable effect
concentration (PEC) above which adverse effects are expected to occur more often
(MacDonald et al. 2000). Meanwhile, mean PEC quotients were calculated by methods of
Long et al. (1998; i.e., for sediment sample, the average of the ratios of concentration of
each contamination to its corresponding PEC was calculated for each sampling position).
Sediment is predicted to be not toxic if mean PEC quotient is < 0.5. In contrast, it is
predicted to be toxic when mean PEC quotient exceeds 1.5 (MacDonald et al. 2000).
43
Sediment quality in this study was also compared with that of other rivers around the
world to see the extent of metal pollution in the To Lich River.
3.2.4.4. Statistical analysis
All statistical analyses were done with statistical significance set at p < 0.05. Cluster
analysis (CA) was employed to classify all nine sampling positions into different clusters,
based on their nearness or similarity (Varol and Şen 2009). In this study, CA was
performed on the data set using Ward’s method with Euclidean distances as a measure of
similarity (Ward 1963).
3.3. RESULTS AND DISCUSSION
3.3.1. Sediment
3.3.1.1. Total organic carbon and heavy metal concentration in sediment
Total organic carbon (TOC) in sediments ranged from 0.5 to 9.7% (Table 3.1), while
concentration of Cr ranged from 55.1 to 805.6 mg kg-1, 267.7 - 1,649.9 for Mn, 9,337 -
187,572 for Fe, 23.3 - 206.7 for Ni, 35.1 - 210.4 Cu, 143.8 - 1,502 for Zn, 14 - 824.5 for
As, 0.8 - 105.2 for Cd, and from 33.2 to 155.5 mg kg-1 for Pb. There was no significant
relationship between TOC or heavy metal level and downstream distances (Table 3.1) as
well as sediment depths (Fig. 3.2). The concentration of heavy metals was observed to be
decreased by sediment depths and increase toward downstream distance in Ganges and
Brahmaputra Rivers of India (Subramanian et al. 1987) and in sedimentary basin of
Finland (Vallius 1999) as a result of gradual accumulation of heavy metals from
industrial and agriculture sources. This study is different, since the To Lich River is quite
short (approximate 17 km) and higher water flow rate therefore wastewater may take only
a few days to flow down to Nhue River through Thanh Liet Dam (Fig. 3.1). The same
phenomenon was concluded by Pease et al. (2007) for study in Tar River floodplain that
downstream correlations for heavy metals were not found.
44
Table 3.1. Concentration of heavy metals (mg kg-1), total organic carbon (TOC, %), and mean probable effect concentration quotients (mPECq) for
each sampling position in the To Lich River, Hanoi
Sampling position
Distance from upstream (km)
Sediment depth (cm)
TOC Cr Mn Fe Ni Cu Zn As Cd Pb mPECq
S1
0.2 0-30 4.9 55.1 1,354.5 187,572.6 70.4 106.9 593.7 824.5 1.2 106.2 4.0
30-60 3.8 82.3 1,398.4 157,842.2 93.4 147.8 512.9 677.5 1.5 155.5
60-90 4.1 66.8 1,649.9 164,753.1 63.2 130.3 702.8 705.8 1.4 152.7
S2
3.1 0-30 4.1 174.0 455.1 16,125.0 48.3 125.2 568.1 24.9 1.1 90.5 0.9
30-60 4.6 186.4 378.7 11,651.2 50.9 98.9 427.0 16.9 0.8 59.1
60-90 5.8 217.0 319.3 9,443.0 45.5 82.0 478.3 19.1 0.9 66.0
90-120 4.8 338.6 414.9 15,338.8 60.9 108.2 580.3 25.3 1.2 88.1
S3
5.1 0-30 3.7 98.1 499.4 15,323.5 62.7 156.0 718.1 19.3 1.9 82.3 1.1
30-60 3.1 181.2 706.8 26,479.9 90.5 146.6 784.8 28.1 2.7 99.6
60-90 3.5 163.1 662.5 24,084.7 83.3 154.6 881.4 26.9 2.4 98.5
90-120 3.1 136.5 574.9 20,984.9 73.1 129.8 698.1 24.6 2.2 81.3
S4
9.1 0-30 4.7 107.9 528.4 17,809.9 111.4 112.5 609.5 21.1 6.4 64.0 2.1
30-60 8.1 173.1 524.0 21,919.3 102.3 210.4 1,212.4 48.5 105.2 124.3
60-90 5.1 141.3 434.0 18,066.6 107.0 140.3 769.6 27.2 20.7 103.9
90-120 6.4 91.4 267.7 9,337.2 72.7 95.6 540.9 18.9 9.0 76.8
S5
13.6 0-30 2.7 77.1 350.7 16,590.7 44.3 59.5 354.8 19.8 0.8 49.4 1.8
30-60 4.7 805.6 477.0 24,206.1 206.7 189.5 1,502.0 68.2 3.6 97.5
60-90 3.7 587.6 500.5 22,590.4 179.2 151.7 1,026.8 43.3 2.2 88.8
45
Table 3.1 (Continued)
S6
13.8 0-30 2.0 118.1 520.7 24,073.3 92.9 81.7 408.9 21.3 9.7 74.0 0.7
30-60 1.0 78.1 567.8 19,719.9 62.2 52.5 212.8 14.9 1.6 56.0
60-90 0.5 74.0 627.5 23,535.2 51.1 39.1 143.8 14.0 0.8 46.0
S7
15.5 0-30 1.7 108.2 574.4 21,313.4 62.9 66.3 356.9 20.5 11.8 57.3 1.1
30-60 2.2 157.2 503.1 21,857.2 77.5 81.8 468.1 26.8 14.5 68.6
S8 15.7 0-30 2.6 95.5 912.6 148,912.1 72.6 65.3 305.2 501.8 2.5 85.7 1.8
30-60 1.7 72.7 753.0 28,451.6 56.9 50.0 192.2 44.8 1.9 64.6
S9 16.3 0-30 9.7 84.8 311.1 20,590.1 23.3 35.1 502.1 42.0 1.2 33.2 0.6
mPECq < 0.5, sampling positions are predicted to be not toxic to aquaculture life; mPECq > 1.5, they are predicted to be toxic (Macdonald et al. 2000).
46
Se
dim
ent
laye
r (c
m)
Mean concentration (mg kg-1)
Fig. 3.2 Relationship between sediment depth and mean concentration of heavy metal
3.3.1.2. Contamination indices
Enrichment factor (EF) and Geo-accumulation index (GI) were matching in explaining
contamination degrees of heavy metals in this study (Table 3.2). Generally, if EF values
were lower than 5 (moderate enrichment) then corresponding values of GI were lower
than 3 (moderately contaminated). The lowest contaminated metal was Mn for all
sediment layers, which owned EF values of 0.3-1.9 (no or minor enrichment)
corresponding to GI values of minus 2.3 to 0.4 (uncontaminated). Meanwhile, Cd was the
highest contaminated metal with GI value of 7.9, corresponding to EF value of 754.8
(Table 3.2). There were no metals causing heavily contaminated at all sampling positions
(Table 3.2; Fig. 3.3). Except Mn and Fe, all other heavy metals caused contamination at
some extents for specific sampling positions and/or sediment layers. Pb caused moderate
to heavy contamination for 11.5% of sediment samples, Zn caused 34.6% samples
moderate to heavy contamination and 7.7% samples heavy contamination, and As caused
3.8 and 11.5% samples heavy to extreme contamination and extreme contamination,
respectively. Meanwhile, 89% samples were contaminated with Cd at moderate to
extreme level (Fig. 3.3). There were two sampling position S1 and S4 (Table 3.2) under
extreme contamination based on maximum GI value, three under heavy to extreme (S6,
0 125 250
90-120
60-90
30-60
0-30 Cr
0 250 500 750
90-120
60-90
30-60
0-30 Mn
0 62.5 125
90-120
60-90
30-60
0-30 Ni
0 62.5 125
90-120
60-90
30-60
0-30 Cu
0 250 500 750
90-120
60-90
30-60
0-30 Zn
0 125 250
90-120
60-90
30-60
0-30 As
0 12.5 25
90-120
60-90
30-60
0-30 Cd
0 62.5 125
90-120
60-90
30-60
0-30 Pb
0 750 1500 2250
90-120
60-90
30-60
0-30 Total
47
S7, and S8), while S5 were under heavy, S3 under moderate to heavy, and S2 and S9
under moderate contamination. Patterns of relationship between heavy metal
contamination degree (GI) and downstream distance and/or sediment depths were also not
found, indicating the dynamics of heavy metals, water regime, etc., of the To Lich River.
Fig. 3.3 Percentage of samples of enrichment (a) and of geo-accumulation (b) classes
0
20
40
60
80
100
Cr Mn Fe Ni Cu Zn As Cd Pb
Sam
ple
perc
enta
geNo enrichment Minor enrichmentModerate enrichment Moderately severe enrichmentSevere enrichment Very severe enrichment
0
20
40
60
80
100
Cr Mn Fe Ni Cu Zn As Cd Pb
Sam
ple
perc
enta
ge
Practically uncontaminated Uncontaminated to moderately contaminated
Moderately contaminated Moderately to heavily contaminated
Heavily contaminated Heavily to extremely contaminated
Extremely contaminated
(a)
(b)
48
Table 3.2. Enrichment factor (EF) and Geo-accumulation index (GI) of heavy metals for sediments in the To Lich River, Hanoi, using Fe as
background value
Sampling position
Sediment depth (cm)
Cr Mn Fe Ni Cu Zn As Cd Pb Contamination levela
EF GI EF GI EF GI EF GI EF GI EF GI EF GI EF GI EF GI
S1
0-30 0.2 -1.3 0.4 0.1 1.0 1.4 0.3 -0.5 0.6 0.7 1.6 2.1 16.0 5.4 1.0 1.4 1.3 1.8 extreme
30-60 0.3 -0.7 0.5 0.1 1.0 1.2 0.4 -0.1 1.0 1.1 1.6 1.8 15.6 5.1 1.5 1.8 2.3 2.4
60-90 0.2 -1.0 0.6 0.4 1.0 1.2 0.3 -0.7 0.8 0.9 2.1 2.3 15.6 5.2 1.3 1.6 2.2 2.3
S2
0-30 5.7 0.4 1.6 -1.5 1.0 -2.1 2.1 -1.1 8.1 0.9 17.5 2.0 5.6 0.4 10.6 1.3 13.2 1.6 moderate
30-60 8.4 0.5 1.8 -1.8 1.0 -2.6 3.0 -1.0 8.9 0.6 18.2 1.6 5.3 -0.2 11.2 0.9 12.0 1.0
60-90 12.0 0.7 1.9 -2.0 1.0 -2.9 3.3 -1.2 9.1 0.3 25.2 1.7 7.3 0.0 15.7 1.1 16.5 1.1
90-120 11.6 1.3 1.5 -1.6 1.0 -2.2 2.8 -0.7 7.4 0.7 18.8 2.0 6.0 0.4 12.2 1.4 13.6 1.6
S3
0-30 3.4 -0.5 1.8 -1.4 1.0 -2.2 2.8 -0.7 10.7 1.2 23.3 2.3 4.6 0.0 19.7 2.1 12.7 1.5 moderate to heavy 30-60 3.6 0.4 1.5 -0.9 1.0 -1.4 2.4 -0.2 5.8 1.1 14.7 2.5 3.9 0.5 15.8 2.6 8.9 1.7
60-90 3.6 0.3 1.5 -0.9 1.0 -1.6 2.4 -0.3 6.7 1.2 18.2 2.6 4.0 0.5 15.8 2.4 9.6 1.7
90-120 3.4 0.0 1.5 -1.1 1.0 -1.8 2.4 -0.5 6.5 0.9 16.5 2.3 4.3 0.3 16.2 2.3 9.1 1.4
S4
0-30 3.2 -0.3 1.6 -1.3 1.0 -2.0 4.3 0.1 6.6 0.7 17.0 2.1 4.3 0.1 56.7 3.8 8.5 1.1 extreme
30-60 4.1 0.4 1.3 -1.3 1.0 -1.7 3.2 0.0 10.1 1.6 27.5 3.1 8.0 1.3 754.8 7.9 13.4 2.1
60-90 4.1 0.1 1.3 -1.6 1.0 -2.0 4.1 0.1 8.1 1.1 21.2 2.4 5.5 0.5 180.4 5.5 13.6 1.8
90-120 5.1 -0.6 1.6 -2.3 1.0 -2.9 5.4 -0.5 10.7 0.5 28.8 1.9 7.4 0.0 151.1 4.3 19.4 1.4
S5
0-30 2.4 -0.8 1.2 -1.9 1.0 -2.1 1.9 -1.2 3.8 -0.2 10.6 1.3 4.3 0.0 7.8 0.9 7.0 0.7 heavy
30-60 17.5 2.6 1.1 -1.4 1.0 -1.5 5.9 1.0 8.2 1.5 30.8 3.4 10.2 1.8 23.4 3.0 9.5 1.7
60-90 13.6 2.1 1.2 -1.3 1.0 -1.6 5.5 0.8 7.0 1.2 22.6 2.8 7.0 1.2 15.3 2.3 9.3 1.6
49
Table 3.2 (Continued)
S6
0-30 2.6 -0.2 1.2 -1.3 1.0 -1.6 2.7 -0.1 3.6 0.3 8.4 1.5 3.2 0.1 63.5 4.4 7.3 1.3 heavy to extreme 30-60 2.1 -0.8 1.6 -1.2 1.0 -1.8 2.2 -0.7 2.8 -0.4 5.4 0.6 2.7 -0.4 13.1 1.9 6.7 0.9
60-90 1.6 -0.9 1.5 -1.0 1.0 -1.6 1.5 -1.0 1.7 -0.8 3.0 0.0 2.2 -0.5 5.2 0.8 4.6 0.6
S7
0-30 2.7 -0.3 1.5 -1.2 1.0 -1.7 2.0 -0.7 3.3 0.0 8.3 1.3 3.5 0.1 87.0 4.7 6.3 0.9 heavy to extreme 30-60 3.8 0.2 1.3 -1.3 1.0 -1.7 2.5 -0.4 3.9 0.3 10.6 1.7 4.4 0.5 104.7 5.0 7.4 1.2
S8
0-30 0.3 -0.5 0.3 -0.5 1.0 1.1 0.3 -0.5 0.5 0.0 1.0 1.1 12.2 4.7 2.7 2.5 1.4 1.5 heavy to extreme 30-60 1.3 -0.9 1.5 -0.8 1.0 -1.3 1.4 -0.8 1.8 -0.4 3.4 0.4 5.7 1.2 10.6 2.1 5.4 1.1
S9 0-30 2.2 -0.7 0.8 -2.0 1.0 -1.8 0.8 -2.1 1.8 -0.9 12.1 1.8 7.4 1.1 8.9 1.4 3.8 0.1 moderate
GI ≤0 is practically uncontaminated, 0<GI≤1 is uncontaminated to moderate, 1<GI≤2 is moderate, 2<GI≤3 is moderate to heavy, 3<GI≤4 is heavy, 4<GI≤5 is
heavy to extreme, and GI>5 is extremely contaminated.
EF 1≤ indicates no enrichment, 1<EF≤3 is minor, 3<EF≤5 is moderate, 5<EF≤10 is moderately severe, 10<EF≤25 is severe, 25<EF≤50 is very severe, and
EF>50 is extremely severe enrichment. a based on highest value of GI at each sampling position. Bold and underline numbers are highest values of GI corresponding to each sampling position.
50
3.3.1.3. Sediment quality comparison
Comparing heavy metal data set of the To Lich River (TLR) with that of other rivers
around the world (Table 3.3), the result indicated that degree of metal contamination in
this study was not more serious than that in Danube River (Europa), Rimac River (Peru),
Tees River (UK), Shing Mun River (Hong Kong), and South Platte River (USA), but
much worse than that of Almendares River (Cuba), Gomti River (India), Nile River
(Egypt), and Yangtze River (China).
Table 3.3. Maximum concentrations of Cr, Mn, Ni, Cu, Zn, As, Cd, and Pb in sediment of
the To Lich River, Hanoi and other selected rivers around the world
Location Maximum concentrations (mg kg-1) References
Cr Mn Ni Cu Zn As Cd Pb
To Lich River, Hanoi
850.6 1,649.9 206.7 210.4 1,502.0 824.5 105.2 155.5 This study
Danube River, Europa
556.5 1,655.0 173.3 8,088.0 2,010.0 388.0 32.9 541.8 Woitke et al. (2003)
Rimac River, Peru 71.0 - 23.0 796.0 8,076.0 1,543.0 31.0 2,281.0 Mendez (2005)
Tees River, UK - 5,240.0 - 76.9 1,920.0 - 6.0 6,880.0 Hudson-Edwards et al. (1997)
Shing Mun River, Hong Kong
66.0 - - 1,660.0 2,200.0 - 47.0 345.0 Sin et al. (2001)
South Platte River, USA
71.0 6,700.0 - 480.0 3,700.0 31.0 22.0 270.0 Heiny and Tate (1997)
Almendares River, Cuba
23.4 - - 420.8 708.8 - 4.3 189.0 Olivares-Rieumont et al. (2005)
Gomti River, India 88.7 834.7 76.1 245.3 343.5 - 17.8 156.3 Sigh et al. (2005)
Nile River, Egypt 274.0 2,810.0 112.0 81.0 221.0 - - 23.2 Rifaat (2005)
Yangtze River, China
205.0 - - 129.0 1,142.0 29.9 3.4 98.0 Yang et al. (2009)
In terms of Zn concentration, 69% sediment samples exceeded maximum permissible
concentration (MCC) for crops, while Cd, Ni, and Cr concentrations exceeded 30.8, 11.5,
and 7.7% samples, respectively (Table 3.4). This indicated that Zn, Cd, Ni, and Cr are
likely to affect crops, which are grown and regularly irrigated with mixture of water and
suspended sediment of TLR. Meanwhile, 100% samples exceeded possible effect
concentration (PEC) for Cu, that were 84.6, 69.2, 50.0, 34.6, 26.9 and 7.7 for Ni, Zn, Cr,
As, Cd and Pb, respectively (Table 3.4). This reveals that the aquatic life is also likely to
be affected, especially for organisms living close and/or in sediment. If sediment is
exposed improperly, it may also affect other terrestrial organisms as well.
51
Table 3.4. Comparison between sediment quality guidelines (SQGs) with heavy metal
concentration (mg kg-1) of all sampling positions in the To Lich River, Hanoi
Cr Ni Cu Zn As Cd Pb
SQGs MCC1 400.0 110.0 200.0 450.0 - 3.00 300.0
TEC2 43.4 22.7 31.6 121.0 9.8 0.99 35.8
PEC2 111.0 48.6 31.6 459.0 33.0 4.98 128.0
This study
% of samples > MCC
7.7
11.5
3.8
69.2
-
30.8
0
% of samples < TEC
0
0
0
0
0
15.4
3.8
% of samples > PEC
50.0
84.6
100.0
69.2
34.6
26.9
7.7
1 Maximum permissible concentrations of potentially toxic heavy metal for crops (Steve 1994). 2 MacDonald et al. (2000), TEC is threshold effect concentration and PEC is probable effect concentration.
Mean PEC quotients (mPECq) were used to evaluate the toxicity for sampling positions
(Table 3.1). In this study, mPECq for all nine sampling positions ranged from 0.6 to 4.0.
The lowest value of mPECq (0.6, not toxic) was observed for site 9, which was located
after Thanh Liet Dam and close to Nhue River. Probably, condition here was more or less
the same that of Nhue River, which has been considered not as contaminated as TLR
(Kikuchi et al. 2009). The highest value of mPECq (4.0, toxic) accompanied with the
highest concentrations of As (824.5 mg kg-1) and Pb (155.5 mg kg-1) was found in S1
(Table 3.1) which was located in residential area without appearance of industrial. The
discharge of water from West Lake, where many uncontrollable activities have been
happening, may be responsible for such situation. In total nine sampling positions, there
were four positions (S1, S4, S5, and S8) predicted to be toxic for aquatic life since
mPECqs exceeded 1.5, the rest five positions were in between > not toxic and < toxic
(MacDonald et al. 2000).
3.3.1.4. Cluster analysis and correlation coefficients
Cluster analysis (CA) was used to group the similar sampling positions (spatial
variability) and to identify specific contamination areas (Simeonov et al. 2000; Casado-
Martinez et al. 2009; Yang et al. 2009; Sundaray et al. 2011). Spatial CA rendered all
nine sampling positions along the To Lich River in a dendrogram based on metal
concentrations in sediment, which were grouped into three statistically significant clusters
52
(Fig. 3.4). Cluster 1 consisted of three sites (sites 3, 4 , and 5; Fig. 3.1), cluster 2
contained sites 2, 6, 7, 8, and 9, and there was only site 1 in cluster 3. Each cluster
presents the similar characteristic features of its sites such as contamination level (Rath et
al. 2009; Chung et al. 2011). Cluster 1 corresponded to moderately contaminated site,
where had mix inputs of industry, hospital, and domestic wastewaters. Cluster 2
corresponded to lowest contaminated sites, even those sites (sites 6, 7, 8, and 9) are
located at downstream section, where many industrial factories discharge untreated
wastewater to river. Low contamination of such sites resulted from Thanh Liet Dam
controlling (Fig. 3.1) which may bring all sediment to Nhue River because of high water
flow rate up to 45 m3/s, when the dam gate opens. Cluster 3 corresponded to highest
contaminated site as result of discharge of wastewater from West Lake (Fig. 3.1) where
was reported that there have been many uncontrollable activities carried out.
Linkage distance (Euclidean)
Fig. 3.4 Dendrogam showing clusters of sediment sampling positions along the To Lich
River, Hanoi
There were strong positive correlations for some pairs of heavy metal in sediments; Fe-As
(r = 0.99), Mn-Fe (r = 0.92), Mn-As (r = 0.91), Cu-Zn (r = 0.89), Cr-Ni (r = 0.8), Ni-Zn
(r = 0.75), Cu-Pb (r = 0.72), and Cr-Zn (r = 0.71). Subramanian et al. (1987) and Caliani
et al. (1997) had the same conclusion for such pairs of metal correlation for studies in
Ganges and Brahmaputra River India, and Huelva Atlantic Spain, respectively.
Meanwhile, strong positive relationships between TOC in water and heavy metals in
0 100 200 300 400 500 600 700
Site 1
Site 8
Site 6
Site 7
Site 2
Site 9
Site 3
Site 4
Site 5
Cluster 3
Cluster 2
Cluster 1
53
sediment (Table 3.5) were also found for Mn (0.75), Pb (0.73), As (0.61) and Ni (0.60),
implying that increase TOC in water leads to increase concentration of those metals in
sediment. The same phenomenon was found by Facetti et al. (1998), since organic
compounds have metal binding properties (Bolt and Bruggenwert 1976). In terms of pair
relationships of TOC and metals in water and that in sediments (Table 3.5), there were
negative relationships (increase concentration in water leads to decrease that in sediment)
for Pb (-0.73), Cu (-0.63) and TOC (-0.59), and positive relationship for Mn (0.70). The
same phenomenon was found for River Rhine floodplain in the Netherlands (Middelkoop
et al. 2002), since discharge affects sedimentation, and then heavy metal deposition.
Table 3.5. Correlation coefficients of total organic carbon (TOC) in water and metals in
sediment, and of TOC and metals in sediment with that in water of the To Lich River,
Hanoi
TOC Cr Mn Ni Cu Zn As Cd Pb
TOC in water with metals in sediment
- 0.02 0.75 0.60 0.46 0.17 0.61 0.05 0.73
TOC and metals in sediment with that in water
-0.59 0.27 0.70 -0.26 -0.63 0.35 0.20 - -0.73
3.3.1.5. Possible sources of heavy metals of sediment profile
Generally Table 3.6 and Fig. 3.5 show possible sources of each sediment layers. For 30-
60 and 60-90 cm sediment layers, they were forming the same metals in clusters and in
factors, it indicated that metals in those two layers has the same possible sources as
discussed in Fig.3.5. While, it was much different for 90-120 cm layer, which formed
only two factors in principal component analysis. For 0-90 cm layers, As, Fe, Mn, and Pb
came from mix of both anthropogenic and natural sources, while Mn, Fe, Cu, and Zn in
90-120 cm layer may come from mix sources. In the past, corresponding to 90-120 cm
layer, Pb came most from anthropogenic source because of using Pb blended gasoline by
old types of vehicles, which may emitted much amount of Pb. In recent years,
corresponding to 0-90 cm layers the source for metal is more or less the same. This may
be because of gradual increasing of the manufacturing activities of industrial zones as
result of economic development processes.
54
Table 3.6. Statistical results of factor analysis
a. Matrix to be factored C
r
Mn
Fe
Ni
Cu
Zn
As
Cd
Pb
Sed
imen
t layer
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
0-3
0
30
-60
60
-90
90
-120
Cr
1
1
1
1
Mn
-0.5 -0.3 -0.3
0.14 1
1
1
1
Fe
-0.6 -0.2 -0.3
0.18
0.98
0.97
0.98
0.99 1
1
1
1
Ni
-0.0
0.92
0.85 -0.9
0.11 -0.0 -0.2
0.05
0.00 -0.0 -0.2
0.01 1
1
1
1
Cu
0.28
0.47
0.40
0.02
0.09
0.06
0.15
0.99 -0.0
0.10
0.16
0.98
0.02
0.66
0.64
0.17 1
1
1
1
Zn
0.06
0.77
0.60 -0.1
0.28 -0.2
0.04
0.96
0.16 -0.2
0.07
0.95
0.15
0.86
0.76
0.30
0.95
0.89
0.97
0.99 1
1
1
1
As
-0.5 -0.2 -0.3
0.71
0.98
0.95
0.96
0.79
0.99
0.99
0.99
0.82 -0.0
0.00 -0.2 -0.5
0.00
0.12
0.17
0.71
0.18 -0.1
0.08
0.61 1
1
1
1
Cd
0.16 -0.1 -0.1 -0.7 -0.1 -0.2 -0.2 -0.7 -0.2 -0.1 -0.2 -0.8
0.82
0.03
0.24
0.57 -0.2
0.60
0.32 -0.7 -0.2
0.45
0.23 -0.6 -0.3 -0.1 -0.2 -1.0 1
1
1
1
Pb
0.03 -0.0 -0.1
0.97
0.75
0.76
0.77
0.37
0.69
0.76
0.81
0.41 -0.0
0.29
0.13 -0.9
0.54
0.68
0.67
0.25
0.55
0.35
0.56
0.12
0.70
0.76
0.81
0.85 -0.2
0.33
0.18 -0.8 1
1
1
1
55
Table 3.6 (Continued)
b. Rotated loading matrix (VARIMAX Gamma = 1.000)
Sediment layer
0-30 30-60 60-90 90-120
PC1 PC2 PC3 PC1 PC2 PC3 PC1 PC2 PC3 PC1 PC2 PC3
Cr -0.70 0.33 0.00 -0.21 0.96 -0.13 -0.35 0.83 -0.35 0.00 1.00 0
Mn 0.97 0.21 0.03 0.97 -0.14 -0.07 0.97 -0.10 -0.12 0.99 0.14 0
Fe 0.98 0.09 -0.07 0.99 -0.07 -0.08 0.98 -0.07 -0.09 0.98 0.18 0
Ni 0.07 0.08 0.97 0.06 0.98 0.05 -0.18 0.92 0.03 0.19 -0.98 0
Cu -0.10 0.97 -0.05 0.22 0.65 0.70 0.30 0.83 0.37 1.00 0.01 0
Zn 0.10 0.94 0.01 -0.09 0.86 0.49 0.19 0.93 0.22 0.99 -0.11 0
As 0.98 0.11 -0.10 0.98 -0.05 -0.07 0.98 -0.05 -0.08 0.70 0.70 0
Cd -0.19 -0.17 0.92 -0.13 -0.03 0.97 -0.15 0.11 0.94 -0.69 -0.72 0
Pb 0.59 0.67 -0.12 0.84 0.22 0.48 0.88 0.33 0.30 0.23 0.97 0
Eigenvalues 3.7 2.5 1.8 3.7 3.1 1.9 3.9 3.2 1.3 5.0 3.9 0
% total variance 42.2 27.8 20.4 41.4 34.8 21.6 44.1 36.2 14.7 55.5 44.4 0
56
Sediment layer
Cluster analysis (Dendrogram using Ward’s method)
Principle component analysis (Factor loadings plot)
0-30
Linkage distance (Pearson)
There were two clusters forming in 0-30 cm layer sediment. Cluster 1 was from Pb, Mn, Fe, and As with quite high correlation coefficients of metal pairs (Table 3.6). In cluster 2, two sub-clusters were formed. The first one was from Ni and Cd, and the second one was from Cr, Cu, and Zn. The pair metal correlation coefficients in cluster 2 were rather weaker than that in cluster 1 (Table 3.6).
Three factors were formed in 0-30 cm sediment layer. Factor 1 contributed 42% variance containing Mn, Fe, As, Cr, and Pb. Those metals corresponded to mix source of both natural source for Mn, Fe, and As and anthropogenic source for Cr (mechanical) and Pb (vehicle emission). Factor 2 contributed 27% variance consisting of Cu, Zn and Pb, those from anthropogenic source of fertilizing and fertilizer manufacturing for Cu and Zn and vehicle emission for Pb. Factor 3 contributed 20% variance including Ni and Cd from anthropogenic source.
30-60
Linkage distance (Pearson)
Cluster Tree
0123
Distances
AsFe
Mn
Pb
Zn
Cu
Cr
CdNi
-1.0
-0.5
0.0
0.51.0
Factor 1
-1.0
-0.5
0.0
0.5
1.0
Factor 2
-0.5
0.0
0.5
1.0
Fac
tor
3
As
Cd
Cr
CuFe
Mn
Ni
Pb
Zn
Cluster Tree
01234
Distances
MnFe
As
Pb
Cd
Cu
Zn
NiCr
-1.0
-0.5
0.0
0.51.0
Factor 1
-1.0
-0.5
0.0
0.5
1.0
Factor 2
-0.5
0.0
0.5
1.0
Fac
tor
3
As
Cd
Cr
Cu
FeMn
Ni
PbZn
57
There were two clusters forming for all concerned metals in 30-60 cm sediment layer. Cluster 1 was formed by As, Fe, Mn and Pb, in which those three former metals had high correlation coefficients (Table 3.6). High correlation coefficients were found for pairs of Ni-Cr and Zn-Cu, those four metals combined with Cd to form cluster 2 in 30-60 cm sediment layer.
Factor 1 contributed 41% of variance including 4 metals; Mn, Fe, As, and Pb (Table 3.6), which may originate from mix source of both anthropogenic and nature. Factor 2 contributed 34% variance containing Cr, Ni and Zn, and factor 3 contributed 21% variance containing Cu and Cd. Those five metals in factor 2 and 3 mainly came from anthropogenic sources such as mechanical industrial, fertilizer manufacturing, leathering painting, etc.
60-90
Linkage distance (Pearson)
The 60-90 cm sediment layer showed the same result of cluster analysis as in 30-60 cm, including two clusters of the same metals in each cluster with more or less the same correlation coefficients for pair of corresponding metals (Table 3.6)
Corresponding to the same metals in clusters, there were also the same metals in factor analysis of 60-90 cm and that of 30-60 cm. This indicated that the possible sources of metals of those two sediment layers were more or less the same. Probably, the manufacturing activities of five industrial zones located in inner Hanoi city were the same at the time corresponding to 30-60 and 60-90 cm sediment layer, probably 8-10 years ago.
Cluster Tree
01234
Distances
MnFe
As
Pb
Cd
Cu
Zn
NiCr
-1.0
-0.5
0.0
0.51.0
Factor 1
-1.0
-0.5
0.0
0.5
1.0
Factor 2
-0.5
0.0
0.5
1.0
Fac
tor
3
As
Cd
Cr
Cu
FeMn
Ni
PbZn
58
90-120
Linkage distance (Pearson)
There were two main clusters formed for nine concerned metals in 90-120 cm sediment layers. Cluster 1 was formed by seven metals, in which they formed two sub-clusters. The first sub-cluster was formed by As, Pb, and Cr with quite high correlation coefficient between metal pair (Table 3.6). The second sub-cluster was formed by Fe, Mn, Cu, and Zn with correlation coefficients of metal pair > 0.95. Meanwhile, Ni and Cd formed cluster 2 separately, which had quite low correlation coefficient of 0.57.
Unlike other sediment layers, factor analysis in 90-120 cm sediment layer indicated that metals formed only two factors. Factor 1 contributed 56% variance containing Mn, Fe, Cu and Zn, those metals may respond to the mix source of both anthropogenic and nature as Mn and Fe mainly from nature and Cu and Zn mainly from industrial like fertilizing and fertilizer manufacturing, and mechanical industrial. Factor 2 contributed 44% variance including Cr, Ni, As, Pb and Cr, which mainly came from industrial sources such as painting, leathering, mechanical and vehicle emission.
Fig. 3.5 Factor loadings plot and Dendrogram of different sediment layer
3.3.2. Surface water
3.3.2.1. Chemical properties and comparison with water quality guidelines
The results of pH, total organic carbon (TOC), and metal concentrations in water are
shown in Table 3.7. There was not much difference among sampling positions in term of
pH, ranging from 7.2 to 7.5. The difference became clearer for TOC, ranging from 4.3 to
10.7 with the mean of 7.7 mg L-1. The highest TOC belonged to S1, where flow rate was
quite low and high TOC seemed to be resulted from household wastewater discharge.
While, the lowest TOC was at S9, which may be attributed to high water flow rate from
opening Thanh Liet Dam. TOC at other sampling positions in the mid-section of the river
Cluster Tree
01234
Distances
CrPb
As
Fe
Mn
Cu
Zn
NiCd
-1.0
-0.5
0.0
0.51.0
Facto 1
-1.0
-0.5
0.0
0.5
1.0
Factor 2
-0.5
0.0
0.5
1.0
Fac
tor
3
As
Cd
CrCu
FeMn
Ni
Pb
Zn
59
was more or less equal. The concentrations of Cr, Ni, Cu, Zn, As, Cd, and Pb at all nine
sampling positions were lower than permitted concentrations for irrigation water (WHO
2006) and acute value for protecting aquatic life (USEPA 2006), meanwhile
concentration of Mn at seven of nine sampling positions except S2 and S6 exceeded
irrigation water standard (WHO 2006). Mn concentration was much different depending
on sampling positions, lowest concentration (83.7 µg L-1) at S2 and highest (430.6 µg L-1)
at S1. Again, uncontrollable activities in West Lake may be responsible for such high
concentration of Mn in S1 (Fig. 3.1).
Table 3.7. pH value, concentration of TOC (mg L-1) and heavy metals (µg L-1) in water of
the To Lich River, Hanoi
Sampling position
pH TOC Cr Mn Ni Cu Zn As Cd Pb
S1 7.5 10.7 5 430.6 5 4 93 51.7 0.2 7
S2 7.2 4.7 2 83.7 5 5 58 47.3 < 0.2 8
S3 7.3 8.3 2 400.8 5 4 40 76.2 < 0.2 7
S4 7.2 7.7 2 230.7 8 3 36 13.1 < 0.2 6
S5 7.3 8.8 5 211.4 8 3 93 41.4 < 0.2 7
S6 7.3 8.1 5 188.7 9 7 60 38.2 < 0.2 8
S7 7.2 7.8 2 200.9 7 4 28 28.1 < 0.2 10
S8 7.2 8.5 3 211.4 6 3 42 36.2 < 0.2 8
S9 7.3 4.3 2 201.7 13 7 52 32.4 < 0.2 11
Mean
±SD 7.3
±0.1 7.7
±2.0 3.1
±1.5 240.0
±108.4 7.3
±2.6 4.4
±1.6 55.8
±23.5 40.5
±17.5 < 0.2
8.0
±1.6
WHO1 6.5-8
100 200 200 200 2,000 100 10 5,000
USEPA2 - - - - 470 13 120 340 2 -
1 Irrigation water standard (WHO, 2006). 2 Acute value for protection of freshwater aquatic life (USEPA 2006).
3.3.2.2. Cluster analysis and correlation coefficients
Cluster analysis (CA) grouped nine sampling positions into three clusters based on
similarity between sampling sites in regards of heavy metal concentration in water (Fig.
3.6). Cluster 1, which consisted of sites 1 and 3, mainly had domestic inputs. This cluster
characterized by the highest concentration of Mn and As (Table 3.1), corresponded to
highest contaminated site. Cluster 2 contained six sites (sites 4, 5, 6, 7, 8, and 9) from
midstream to downstream corresponded to moderately contaminated site, where several
manufacturing plants are located. Site 2 alone formed cluster 3 corresponded to lowest
contaminated site.
60
The dissimilarity in clustering metal contaminated degrees between sediment and water
was observed for sites 3, 6, 7, 8, and 9 (Fig. 3.4 and Fig. 3.6). This indicated the
complexity of contamination in sediment and water, since many factors affect metal
concentration in water and metal accumulation in sediment such as the proximity of river
contamination, river activity (flow rate) and the intensity of geomorphic activity of the
river basin (Martin 2000).
Linkage distance (Euclidean)
Fig. 3.6 Dendrogam showing clusters of water sampling positions along the To Lich
River, Hanoi
There were no inter-element correlations in water, except pair of Zn-Cr (r = 0.66). While,
positive linear of inter-element relationship was found for Cu, Pb, Zn, Cr, Ni, As, and Cd
(Subramanian et al. 1987; Caliani, et al. 1997; Bastidas 1999). The heavy metals
discharged to water body in such studies were mostly from natural sources (e.g.
precipitation, parent material decomposition) without or little industrial wastewater,
which is different from the present study area. This may be concluded that manufacturing
plants discharge various heavy metals to the To Lich River, which were not proportional
each other.
3.3.3. Accumulation coefficient
Accumulation coefficients (Dojlido and Taboryska 1991) were calculated as quotient of
the heavy metal concentrations in sediment and that in water. The accumulation
coefficient in the To Lich River (Table 3.8) ranged from 2,609 (Mn) to 57,328 (Cr),
0 50 100 150 200 250
Site 2
Site 5
Site 6
Site 9
Site 8
Site 7
Site 4
Site 3
Site 1
Cluster 3
Cluster 2
Cluster 1
61
following the order of Cr > Cu > Ni > Zn > Pb > As > Mn. This may imply the long
accumulation history of heavy metal in this river.
Table 3.8. Accumulation coefficients of heavy metals in the To Lich River, Hanoi
Cr Mn Ni Cu Zn As Cd Pb
Mean in water
(mg L-1)
0.003
0.240
0.007
0.004
0.056
0.041
na
0.008
Mean in sediment (mg kg-1)
171.985
625.649
79.435
108.366
598.129
127.916
8.048
83.461
Accumulation coefficient
57,328.4
2,606.9
11,347.9
27,091.6
10,680.9
3,119.9
-
10,432.6
Accumulation coefficient equals ratio of mean concentration in sediment to that in water. na data not available.
Accumulation coefficients of Cr, Cu, Zn, and Pb in present study were much higher than
that in Wloclawek reservoir (Dojlido and Taboryska 1991), even concentrations of those
metals in water were much lower and water flow rate was higher than that of the reservoir.
This again indicated that accumulation of heavy metal in sediment is affected by many
factors, beside metal concentration in water and flow rate, such as how they can associate
with others and re-suspend to release to water, etc. (Martin 2000).
3.4. CONCLUSIONS
In the present study, water and sediment analysis was carried out for assessment of heavy
metal pollution in To Lich River (TLR), inner Hanoi city. The results indicated that
concentrations of most heavy metals in water, except Mn, were lower than irrigation
water limit and acute value for protecting aquatic life. Geochemical analysis showed
significant heavy metal concentration in sediments suggesting the anthropogenic impacts
on TLR. The Geo-accumulation index and Enrichment factor of Pb, Zn, As, and Cd
showed that a considerable number of sediment samples were at moderate to extreme
pollution, whereas Mn and Fe were generally within the background levels. Heavy metal
concentration of TLR is at the middle level in comparison with the findings from other
rivers around the world. With respect to sediment quality guidelines, sediments at all sites
exceeded maximum permissible concentrations of potentially toxic heavy metal for crops
and were considered to be harmful for aquatic life. According to mean probable effect
concentration quotients, sediments of sites 1, 4, 5, and 8 are predicted to be toxic to
sediment-dwelling organisms. Cluster analysis suggested that the sediment from TLR can
be significantly distinguished into three groups in terms of contamination degrees.
Accumulation ability of heavy metals in sediment was in order of Cr > Cu > Ni > Zn > Pb
> As > Mn based on accumulation coefficient.
62
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67
CHAPTER 4. DOES EMBANKMENT IMPROVE QUALITY OF A RIVER? A
CASE STUDY IN TO LICH RIVER INNER CITY HANOI, WITH SPECIAL
REFERENCE TO HEAVY METALS
Has been published in Journal of Environmental Protection 2013, Vol. 4, No. 4, pp. 361-
370.
ABSTRACT
To Lich River (TLR) system receives wastewaters from a population of nearly two
million people and 100 manufactories of five industrial zones in inner city Hanoi,
Vietnam. To improve quality of TLR, the embankment was carried out in 1998 and
finished in 2002, resulted in width of 20 - 45 m, depth of 2 - 4 m, and maximum water
flow capacity of 30 m3/s. Water and sediment quality indices based on heavy metal
concentrations were used to evaluate current river environment compared to that of pre-
embankment. Mass balance model was employed to estimate total metal loads for specific
river reaches, which corresponds to various types of wastewater discharged along the
river. The results indicated that currently there is about 284,000 m3 sediment accumulated
in TLR bed, which is under high contamination of Cr, Mn, Fe, Ni Cu, Zn, As, Cd, and Pb
with a total of 7,347 tons of all concerned metals. Domestic-discharged river reaches
received much lower metal loads, roughly 8-28% compared to river reaches of both
domestic and industrial inputs. Total load of all nine concerned metals at the end of TLR
is 161.7 kg/day, which is finally discharged to Nhue River at South Hanoi. Water quality
was improved much right after finishing embankment, then it gradually deteriorated.
Meanwhile, sediment quality became even much worse after embankment. Relative river
quality index as equal weight for both water and sediment quality indices indicated that
quality of TLR was not much improved after the embankment. It even became worse due
to the urbanization in recent years.
Keywords: Industrial discharge, Mass balance, Metal load, River quality index, Sediment
accumulation.
68
4.1. INTRODUCTION
The economic, social, and environmental importance of water resource cannot be
overstated. Water is a vital resource for healthy living conditions and sound ecosystems.
Among the relevant issues that can be analyzed, water quality is quite significant (Schiff
and Winters 2002). Water body of polluted rivers, especially in densely populated cities,
is usually blamed as a critical source of waterborne diseases and others. It is estimated
that approximately one-quarter of the global disease burden and more than one-third of
the burden among children are due to modifiable environmental factors (Saracci and
Vineis 2007; Pruss-Ustun and Corvalan 2007, 2006). Materials, which are widely used in
industries for their physical qualities, have proved carcinogenic, mutagenic and/or
teratogenic in human (Rothman and Greenland 1998; Suser 1991). Those materials are
much responsible for reduce of environmental quality, ecosystem degradation, etc.
Residual of those materials from industries, if managed improperly, is finally discharged
to environment especially water bodies and accumulated in sediment.
Water bodies in a city are usually serving as discharging wastewaters. The health of a
river is much depending on quality of discharged waters to its body. In being urbanized
cities of developing countries, wastewater treatment is not much taken care leading to
over pollution of water bodies. Pollution is facilitated in several respects in urban basins.
First, un- and/or partially treated wastewater from both industry and municipality is
discharged directly. Second, construction generates a number of pollutants that easily
adsorb or dissolve in runoff. Third, high background pollution loads often accumulate in
urban areas between rainy events, mostly from structural deterioration and improper
disposals of solid waste of industry and municipality, and others. Many of those
pollutants easily adsorb to particles suspended in runoff from construction sites as well
(Schueler 1987). The pollution loads often adversely affect water and sediment quality,
and biological communities (Crawford and Lenat 1989, Mason 1981).
Sedimentation is a natural process and represents a fundamental part of ecosystem
functioning that is essential to the health of rivers and water bodies (Guy 1972). Many
human activities such as manufacturing, construction, transportation as a manner of
moving dirty, dramatically increase the rate of erosion, resulting in larger than normal
sediment deposits in inner city rivers with various organic and heavy metal contaminants.
Sediment loads from construction can be 10 - 20 times greater than cultivated lands
(Owen 1975), and its delivery ratios of 0.5 - 1.0 are often reported for urban basins
69
(Simmons 1987, Novotny and Chesters 1989). Those sediment loads often exceed the
natural assimilative and equilibrating capacities of the receiving water systems. The
contaminants of most concern are metals, polyaromatic hydrocarbons, polychlorinated
biphenyls, and mineral oil. Therefore, disposal of polluted dredged sediments on land
may lead to certain risks. Dredging is necessary to increase water flow rate, but also for
remediation, whereas the risk for the environment and health might be high. Meanwhile,
dredging of contaminated sediments faces problem of treatment and disposal of these
contaminated sediments (Bortone et al. 2004). Currently, contaminated dredged
sediments are often not valorisable due to their high content in contaminants and their
consequent hazardous properties. Organics can be destroyed in place, whereas metals are
immutable and relatively immobile. In addition, it is generally admitted that treatment and
reuse of heavily contaminated dredged sediments is not a cost-effective alternative to
confined disposal.
This study aims at (1) evaluating contamination level of sediment and water, and quality
of To Lich River (TLR) after 9 years embankment, (2) estimating total load of total
organic carbon and heavy metals entered and accumulated in sediment in specific river
reaches corresponding to its wastewater sources, and (3) estimating daily discharge of
total organic carbon and heavy metals at the end of TLR.
4.2. MATERIALS AND METHODS
4.2.1. Study site
There are four main rivers forming To Lich River (TLR) system, which receives
wastewaters from inner city of Hanoi and covers a basin area of 77.5 km2 (Nguyen 2005).
To Lich is the biggest river receiving wastewaters from western part of Hanoi, while Kim
Nguu, Set and Lu are three smaller ones receiving wastewaters from eastern part before
discharging to TLR in downstream (Fig. 4.1). TLR originates from West Lake in North
Hanoi, receiving mainly domestic wastewater in upstream and mix of domestic and
industrial wastewater in downstream before joining Nhue River in South Hanoi through
Thanh Liet Dam (Fig. 4.1). The construction of embankment was completed in 2002,
covering most of river reaches. The un-embanked upstream reach, which has a narrow
width of 1 - 4 m, is subjected to convert into a closed sewer. Currently, the embanked
river reaches have a width of 20 - 45 m and depth of 2 - 4 m, and a maximum flow
capacity of 30 m3/s. There are 239 point sources, including both pipe and box culverts
along TLR (Nguyen 2005). Non-point sources are also available, such as illegal dumping
70
practices and urban storm water runoff. In dry season, water released from West Lake is
limited because of low water level. The input flow then is mainly wastewaters from
households and industry with high contaminants (HENRD 2009).
There are five industrial zones located in TLR system basin, in which no suitable
wastewater treatment systems are available (Nguyen 2005). Thuong Dinh industrial zone
consists of 30 manufacturing plants, which have been directly discharging un- and/or
partially treated wastewater to downstream reach of TLR. Those plants include: fourteen
of mechanical industry, four of textile industry, three of leather industry, two of chemical
industry (rubber and soap), two of ceramic industry, one of tobacco industry, one of paper
industry, and three others. Other four industrial zones, including 69 plants of all types of
industries, discharge wastewaters to Lu, Set, and Kim Nguu rivers, before entering TLR
in downstream (Fig. 4.1).
Thanh Liet Dam was built at 0.5 km from downstream to control water flow direction of
TLR (Fig. 4.1). The dam is closed when water level of TLR is lower than that of Nhue
River and/or water of TLR is too polluted, which may affect the agricultural production at
downstream of Nhue River. In such case, water runs to Yen So Lake through downstream
reach of Kim Nguu River and then it is pumped to Red river.
4.2.2. Sample collection
Surface water and sediment of 0-30, 30-60, 60-90, and 90-120 cm depths were collected
at five sites along the river (Fig. 4.1). The first and second sampling sites were located in
embanked river reach, receiving most domestic and hospital wastewater. The third
sampling site was located right before discharge of Thuong Dinh industrial zone. The
fourth and fifth sampling sites were located in un-embanked river reach, after confluence
with Lu and Kim Nguu rivers, respectively. All samples were collected in dry season in
March 4-5, 2011 (no rainy days).
Water samples were collected in pre-cleaned polypropylene bottles and preserved at 4oC
in refrigerator until analysis. For heavy metal determination, the water samples were
acidified with conc. HNO3 to pH < 2. The pH of water was measured in-situ using a
portable pH meter. Meanwhile, sediment samples were taken from river bed using a self-
made sediment sampler and placed into polyethylene bottles.
71
Fig. 4.1 Map of study area showing sampling sites
4.2.3. Chemical analysis
Total organic carbon (TOC) contents in water and sediment were analyzed using a TOC
analyzer (TOC-5000A, Shimadzu). For heavy metal analysis, sediment samples were air-
dried at room temperature and passed through 1 mm stainless steel sieve to remove big
particles. Then the samples were heated in an oven at 60oC until constant weight,
powdered and homogenized. For microwave-assisted acid digestion procedure, roughly
50 mg dry homogenized sediment was weighed into a vessel and successively digested
with 10 mL of conc. HNO3 in a microwave digestion system (USEPA 2007). After
cooling, the digest was transferred into a plastic volumetric flask and adjusted to 50 mL
volume with Mili-Q water. The sample was finally filtered through a membrane filter
(0.45 µm pore size). Concentrations of heavy metals (Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, and
72
Pb) in water and acid-digested sediment samples were determined using an inductively
coupled plasma-mass spectrometry (ICP-MS).
Standard operating procedures, calibration with standards, and analysis of reagent blanks,
and analysis of replicates were used to guarantee the quality of analytical data. Analysis
for all samples was carried out in triplicate to get the mean as final data.
4.2.4. General characteristics of river
Water flow rate (Q; m3/s) at each sampling site was calculated as Q = V ∗ A�, where V is
water velocity (m/s) and Aw is cross-section of water body (m2). V was measured using
FP101-FP201 Global Flow Probe. At each sampling site, three positions across the river
(one in the center, one in each site with distance of 3 m from river banks) were measured
for V to get average value. Tape was used to measure width of water surface across river,
while height stick was used for water and sediment depths (Fig. 4.2). The sediment depth
at each sampling site was just the depth of deepest sediment layer collected (Table 4.1).
Slope of river bank was measured at each sampling site in degree to identify cross-
sectional area of water and sediment bodies (Fig. 4.2).
Area of water cross-section (Aw in m2) at each sampling site was calculated as following
equation:
Aw=((W-2WD*tan(S))+W) * WD/2
=(2W-2WD*tan(S))*WD/2
=(W-WD*tan(S))*WD
=W*WD-WD2*tan(S) (4.1)
where, W is width of water surface in meter, WD is water depth in meter, S is slope of
river bank in degree.
Area of sediment cross-section (As in m2) at each sampling site was calculated following
Eq. 4. 2.
As={((W-2WD*tan(S))-2SD*tn(S))+(W-2WD*tan(S))}*SD/2
={W-2WD*tan(S)-SD*tan(S)}*SD
73
={W-tan(S)*(2WD+SD)}*SD
=SD*W-tan(S)*(2WD*SD+SD2) (4.2)
where SD is sediment depth in meter.
Fig. 4.2 Vertical cross section of To Lich River
4.2.5. Loading of heavy metals
Chemical mass balance model was introduced by Dolan and Shaarawi (1989) to estimate
chemical load in a river reach following Eq. 4. 3.
QdCd-QuCu=� Li
n
i=1 (4.3)
where, Qd and Qu are downstream and upstream flows, Cd and Cu are downstream and
upstream concentrations, and ∑ ��� !" is sum of all individual loadings to river reach. In
fact, river contaminants undergo significant volatilization and/or degradation, therefore to
improve the accuracy Eq. 4. 3 was modified by Jha et al. (2007) as
#$%$ & #'%'()*+ = � ��
,
�!" (4.4)
where, k is coefficient of attenuation rate (day-1), t is travel time (day). #$%$is total load
in downstream and/or at the end of river reach.
4.2.6. River quality index
Water quality index has been widely used to evaluate the quality/pollution levels of rivers
(Liou et al. 2004; Parparov et al. 2006; Bordalo et al. 2006; Banerjee and Srivastava
2009). In this study, we extend this knowledge to evaluate both water and sediment
quality as a base for river quality assessment. In order to evaluate the improvement of
74
river, a water quality index (WQI) and a sediment quality index (SQI) were developed
based on seven parameters modeled (Cr, Mn, Ni, Cu, Zn, As and Pb for water, and Cr, Ni,
Cu, Zn and Pb for sediment).
The WQI and SQI were derived as the following manners:
Indexwatermetali=
Concentration in watermetali in year A
Concentration in watermetali in year B
WQI = ( � Indexwatermetali
7
i=1
)/7
where, Indexwatermetali is quality index of metal i in water, Concentration in watermetali in year A
is concentration in water of metal i in year A, and Concentration in watermetali in year B is
concentration in water of metal i in year B (A > B).
Indexsedimentmetali=
Concentration in sedimentmetali in year A
Concentration in sedimentmetali in year B
SQI = ( � Indexsedimentmetali
5
i=1
)/5
where, Indexsedimentmetali is quality index of metal i in sediment,
Concentration in sedimentmetali in year Aand Concentration in sedimentmetali in year B
are
concentrations in sediment of metal i in year A and B, respectively (A > B).
Subsequently, a simple relative river quality index (RQI) was derived giving equal weight
for both WQI and SQI:
RQI = (WQI + SQI)/2
where, WQI, SQI, and/or RQI equals 1 there is no improvement for water, sediment
and/or river, while it is improved if the values are < 1, and becomes worse if the values
are > 1.
75
4.3. RESULTS
4.3.1. General characteristics of To Lich River
The water velocity gradually increases from up to downstream as 0.015 m/s at S1 to
0.039 at S2, 0.049 at S3, 0.117 at S4, and 0.131 m/s at S5 before discharging to Nhue
River (Table 4.1). Corresponding to water velocity is water flow rate, which also
increases toward downstream as result of various wastewater inputs along TLR (Table 4.1,
Fig. 4.3a). The flow rate at S5 right after confluence with Kim Nguu River was 6.68 m3/s,
nearly doubled that (3.53 m3/s) at S4 located after confluence with Lu River. The same
pattern was found between S3 and S4. Those indicated the high water flow rate from both
Lu and Kim Nguu to TLR.
Table 4.1. General characteristics of specific reaches of To Lich River
Sampling site S1 S2 S3 S4 S5
Distance from upstream (km) 3.1 5.1 9.1 13.8 15.5
Water depth (m) 0.75 0.84 0.98 1.05 1.34
Area of water cross section (m2) 11.91 14.50 23.83 30.25 50.97
Water velocity (m/s) 0.015 0.039 0.049 0.117 0.131
Flow rate (m3/s)1 0.18 0.57 1.16 3.53 6.68
Total travel time in a specific reach (days)2
0.85 1.05 0.66 0.18
Sediment depth (m) 1.2 1.2 1.2 0.9 0.6
Area of sediment cross section (m2) 16.16 18.00 26.57 23.60 21.03
Mean sediment cross sectional area (m2) for a specific reach3
17.08 22.29 25.08 22.31
Total sediment volume in a specific reach (m3)4 34,161 89,139 117,888 42,395
Average sediment density in a specific reach (kg/m3)5
1,053 1,195 1,242 1,357
Estimated cost required for treating sediment (average cost6 of 36 USD/m3)
1,229,784 3,209,020 4,243,957 1,526,227
1 equals to water velocity multiplying area of water cross section. 2 equals to ratio of length (m) to mean of water velocity (m/s) at first and last points of a specific river reach. 3 equals to mean of first and last sediment cross sectional area of a specific river reach. 4 equals to length of river reach multiplying mean sediment cross section. 5 testing dry weight of known volume of sediment. 6 composite unit costs extrapolated from case studies in USA range from a low of approximately 36 USD/m3 to over 600 USD/m3 (Myers 2005).
Since velocity increases toward downstream, travel time of water decreases which takes
0.43 day/km between S1-S2, 0.26, 0.14 and 0.09 day/km between S2-S3, S3-S4 and S4-
S5 river reaches, respectively. As a consequence, sediment also become shallower toward
76
downstream; 1.2 m depth at S1, S2 and S3, 0.9 m at S4, and only 0.6 m at S5 (Table 4.1,
Fig. 4.3b). Based on cross-sectional area of sediment body and length of each river reach,
total sediment accumulated in river bed was estimated. Lowest amount of sediment of
34,161 m3 was observed at reach between S1-S2, then 42,395 between S4-S5, 89,139
between S2-S3, and the highest of 117,888 m3 between S3-S4. Meanwhile, sediment
density increases gradually to downstream (Table 4.1).
Figure 4.3 River characteristics
4.3.2. Sediment quality
High variation of total organic carbon (TOC) and heavy metal concentrations among
sampling sites was found (Table 4.2). TOC content varied between 11 at S4 and 60 g/kg
at S3. Meanwhile, Cr ranged from 90 at S4 to 229 mg/kg at S2; Mn ranged from 392 at
S1 to 610 at S2; Fe ranged from 13,139 at S1 to 22,442 at S4; Ni ranged from 51 at S2 to
98 at S3; Cu ranged from 57 at S4 to 146 at S2; Zn ranged from 255 at S4 to 783 at S3;
As ranged from 16 at S4 to 28 at S3; Cd ranged from 1.0 at S1 to 35 at S3; and Pb ranged
from 58 at S4 to 92 mg/kg at S3. Comparing among heavy metals, the average
concentrations in sediment increased following the order of Cd <As <Ni <Pb< Cu < Cr
<Mn<Zn < Fe (Table 4.2).
Concentrations of Zn and Cd far exceeded the maximum permissible concentrations of
potentially toxic heavy metal for crops after application of sewage sludge (Steve 1994).
Comparing to Vietnamese standard, contents of most concerned heavy metals exceeded
the allowable limit for both agricultural and industrial soils (Table 4.2).
00.020.040.060.080.10.120.14
0
2
4
6
8
S2 S3 S4 S6 S7
Vel
ocit
y (m
/s)
Flo
w r
ate
(m3/
s)
Flow rate Velocity
0
0.5
1
1.5
S2 S3 S4 S6 S7
Dep
th (m
)
Water Sediment
(b) (a)
S1 S2 S3 S4 S5 S1 S2 S3 S4 S5
77
Table 4.2. Mean1 concentration (±SD) of total organic carbon (TOC; g/kg) and heavy
metals (mg/kg) in sediment at specific sampling sites along To Lich River
Sampling site TOC Cr Mn Fe Ni Cu Zn As Cd Pb
S1
48.3
±7.1
229.0
±75.3
392.0
±57.6
13,139.5
±3,142.7
51.4
±6.7
103.6
±18.0
513.4
±73.4
21.6
±4.2
1.0
±0.2
75.9
±15.7
S2
33.5
±3.0
144.7
±36.1
610.9
±92.4
21,718.3
±4820.2
77.4
±12.1
146.8
±12.0
770.6
±82.6
24.7
±3.9
2.3
±0.3
90.4
±10.0
S3
60.8
±15.3
128.4
±36.3
438.5
±121.9
16,783.3
±5,308.0
98.4
±17.5
139.7
±50.6
783.1
±301.8
28.9
±13.5
35.3
±47.0
92.3
±27.1
S4
11.7
±7.6
90.1
±24.4
572.0
±53.5
22,442.8
±2,373.4
68.7
±21.7
57.8
±21.8
255.2
±137.5
16.7
±4.0
4.0
±4.9
58.7
±14.2
S5
19.5
±3.5
132.7
±34.6
538.8
±50.4
21,585.3
±384.5
70.2
±10.3
74.1
±11.0
412.5
±78.6
23.7
±4.5
13.2
±1.9
63.0
±8.0
Mean
34.7
±20.2 145.0
±51.2
510.4
±92.0
19,133.8
±4,034.1
73.2
±17.0
104.4
±39.2
547.0
±229.2
23.1
±4.5
11.2
±14.3
76.1
±15.3
Sampling in 20052
- 570.2 - - 74.0 333.2 390.8 - 9.6 375.3
Sampling in 19973
- 580.1 - - 14.9 158.7 192.7 35.2 - 139.0
QCVN 03: 2008/BTNMT
for agricultural soil4
- - - - - 50 200 12 2 70
QCVN 03: 2008/BTNMT
for industrial soil4
- - - - - 100 300 12 10 300
MCC5 - 400 - - 110 200 450 - 3 300
1 mean of all sediment layers in each sampling site for TOC and specific heavy metal. 2 cited from Nguyen et al. (2010). 3 cited from HSDC (1997). 4 QCVN 03: 2008/BTNMT - Vietnamese technical regulation on the allowable limits of heavy metals in soils. 5 Maximum permissible concentrations of potentially toxic heavy metal for crops after application of sewage sludge (Steve 1994).
There were huge amounts of TOC and heavy metal accumulated in sediment in specific
river reaches (Table 4.3). The highest amount belonged to TOC with a total of 12,745
tons in whole river sediment, followed by Fe of 6,815, Zn of 201, Mn of 179, Cr of 43,
Cu of 38, Pb and Ni of 27 tons each, As of 8, and Cd of 5.4 tons.
78
Table 4.3. Total load of total organic carbon (TOC) and heavy metal in sediment in
specific reaches of To Lich River
River reach Unit TOC Cr Mn Fe Ni Cu Zn As Cd Pb
S1-S2
total (ton)
1,470.3 6.7 18.0 626.9 2.3 4.5 23.1 0.8 0.1 3.0
kg/m3 43.041 0.197 0.528 18.353 0.068 0.132 0.676 0.024 0.002 0.088
S2-S3
total (ton)
5,019.8 14.5 55.9 2,050.6 9.4 15.3 82.8 2.9 2.0 9.7
kg/m3 56.314 0.163 0.627 23.005 0.105 0.171 0.928 0.032 0.022 0.109
S3-S4
total (ton)
5,301.5 16.0 74.0 2,871.7 12.2 14.5 76.0 3.3 2.9 11.0
kg/m3 44.971 0.136 0.628 24.359 0.104 0.123 0.645 0.028 0.024 0.094
S4-S5
total (ton)
896.5 6.4 32.0 1,266.5 4.0 3.8 19.2 1.2 0.5 3.5
kg/m3 21.147 0.151 0.754 29.873 0.094 0.089 0.453 0.027 0.012 0.083
Grand total ton 12,688.2 43.7 179.9 6,815.7 27.9 38.0 201.1 8.2 5.4 27.3
Concentration of TOC and heavy metal as mean of all layers (Table 4.2) at first and last points of specific river reach was used for calculation. Load of TOC and heavy metal equals to mean concentration multiplying total sediment amount corresponding to its density in a specific river reach (Table 4.1).
4.3.3. Water quality
There was not much variation in pH, ranging around 7.2-7.3 among sampling sites.
Meanwhile, high variation was observed for total organic carbon (TOC; Table 4.4), the
highest value found in S2 of 8.3 mg/L nearly doubled that in S1 (4.7 mg/L).
Concentrations of Cr, Ni, Cu, and Pb were lower than 10 µg/L and not much different
among all sampling sites. Meanwhile, that of Zn, As, and Mn were much higher, ranging
from 36 to 60, 13-76, and 83-400 µg/L, respectively. Except Mn, all other heavy metals
were still under recommended levels for irrigation water (Table 4.4).
79
Table 4.4. pH value, concentration of total organic carbon (TOC; mg/L) and heavy metals
(µg/L) in water at specific sampling sites in To Lich River
Sampling site pH TOC Cr Mn Ni Cu Zn As Cd Pb
S1 7.2 4.7 2 83.7 5 5 58 47.3 < 0.2 8
S2 7.3 8.3 2 400.8 5 4 40 76.2 < 0.2 7
S3 7.2 7.7 2 230.7 8 3 36 13.1 < 0.2 6
S4 7.3 8.1 5 188.7 9 7 60 38.2 < 0.2 8
S5 7.2 7.8 2 200.9 7 4 28 28.1 < 0.2 10
Mean ±SD 7.24
±0.05
7.32
±1.48
2.60
±1.34
220.96
±114.80
6.80
±1.79
4.60
±1.52
44.40
±14.03
40.58
±23.61 -
7.80
±1.48
Sampling in 20051 7.3 21.2 8.4 114.0 6.0 4.6 31.6 5.6 - 1.9
Sampling in 19972
- - 13.0 220.0 4.0 20.0 2000.0 66.0 - 160.0
TCVN 5942-1995 B3
5.5-9 - 1,000 800 1,000 1,000 2,000 100 20 100
Irrigation water guidelines4
6.5-8 - 100 200 200 200 2,000 100 10 5,000
Freshwater5 - - 1.0 8.0 0.5 3.0 15.0 0.5 - 3.0
1 cited from Kikuchi et al. (2009). 2 cited from HSDC (1997). 3 Surface water quality standard in Vietnam used for the purpose other than domestic water supply including irrigation water. 4 WHO (2006). 5 Median values of freshwater in the world (Bowen 1979).
Using heavy metal and organic carbon concentrations of sampling sites to apply mass
balance model (Equation 4), total loads of TOC and heavy metal generated to each river
reach and at the end of To Lich River (TLR) before discharging to Nhue River were
estimated (Table 4.5, Fig. 4.4). High variation of loads of TOC and heavy metal was
found among river reaches; ranging from 338 to 2,036 kg/day for TOC, 0.07-1.35 for Cr,
3.25-58.51 for Mn, 0.18-2.04 for Ni, 0.14-1.88 for Cu, 1.25-15.19 for Zn, 3.16-10.49 for
As, and from 0.24 to 3.42 kg/day for Pb. In general, river reaches of S1-S2 and S2-S3 in
upstream, where received mostly domestic wastewater, had lower loads of all heavy
metals and TOC compared to that of S3-S4 and S4-S5 river reaches in downstream (Table
4.5), which received various types of wastewater. TOC discharged from TLR to Nhue
River reached 4,504 kg/day (Table 4.6), while that of heavy metals was much lower; 1.15
kg/day for Cr, 2.31 for Cu, 4.04 for Ni, 5.77 for Pb, 16.17 for Zn, 16.22 for As, and up to
116 kg/day for Mn.
80
Table 4.5. Total heavy metal and organic carbon (TOC) discharged to specific reaches of
To Lich River (kg/day)
Attenuation rate1 River reach
S1- S2 S2- S3 S3- S4 S4- S5
TOC 0 338 360 1,697 2,036
Cr 0.19 0.07 0.12 1.35 -
Mn 0 18.55 3.25 34.40 58.51
Ni 0.21 0.18 0.60 2.04 1.40
Cu 0.25 0.14 0.15 1.88 0.27
Zn 0.24 1.25 2.07 15.19 -
As 0.21 3.16 - 10.49 5.01
Pb 0.19 0.24 0.32 1.91 3.42
1 cited from Ambrose et al. (1991), there are no attenuation rates for TOC and Mn available, the value of zero was used for estimation. Estimated values of Cr and Zn in S4-S5 river reach and of As in S2-S3 river reach were negative, they were excluded.
Figure 4.4 Heavy metal and total organic carbon (TOC) discharged to specific reaches
(kg/day)
0
500
1000
1500
2000
2500
S2-S3 S4-S6
TOC
0
20
40
60
S2-S3 S3-S4 S4-S6 S6-S7
Mn Zn As
0
1
2
3
4
S2-S3 S3-S4 S4-S6 S6-S7
Cr Ni Cu Pb
S1-S2 S2-S3 S3-S4 S4-S5
S1-S2 S2-S3 S3-S4 S4-S5 S1-S2 S2-S3 S3-S4 S4-S5
81
Based on estimated data of population, water supply per capita, and water use in industry
in TLR system basin, discharge of TOC and heavy metals from To Lich to Nhue River
was estimated (Table 4.6). Wastewaters volume increased year by year, from 450,922
m3/day in 2005 to 577,399 m3/day in 2011 and may up to 718,750 m3/day in 2020. This
was accompanied by the increase in heavy metals loaded to Nhue River; Mn of 51.41
kg/day in 2005 to 116 in 2011 and to 144.4 kg/day in 2020, As of 2.53 kg/day in 2005 to
16.22 in 2011 and to 20.20 kg/day in 2020, and other heavy metals (Table 4.6).
Table 4.6. Total load1 of total organic carbon (TOC) and heavy metal at the end of To
Lich River before discharging to Nhue River by year (kg/day)
Year TOC Cr Mn Ni Cu Zn As Pb Water discharge (m3/day)2
20053 9,560 3.79 51.41 2.71 2.07 14.25 2.53 0.86 450,922
20114 4,504 1.15 116.00 4.04 2.31 16.17 16.22 5.77 577,399
20205 5,606 1.44 144.40 5.03 2.88 20.13 20.20 7.19 718,750
1 equals to Qd*Cd (Qd and Cd are downstream discharge and concentration, respectively). 2 at the end of To Lich River. 3 discharge data is citied from Nguyen (2005), while TOC and heavy metal concentrations are cited from Kikuchi et al. (2009). 4 from this study. 5 assuming that TOC and heavy metal concentrations are the same as in this study, while discharge is based on the data of population change and change of freshwater supply per capita in TLR system basin (Nguyen 2005).
4.3.4. River quality
Table 4.7 shows values of water and sediment quality indices of To Lich River (TLR).
The embankment of TLR started in 1998 and finished in 2002. To understand the
efficiency of embankment on river quality, concentrations of heavy metal in water and
sediment in 1997 and in 2005 were used to compare with that in the present study. Water
quality was much improved in 2005 and in 2011 compared to pre-embankment as water
quality index of pair of 2005-1997 was 0.43 and that of 2011-1997 was 0.55. However,
quality of water in 2011 became worse than that in 2005. Conversely, sediment quality
became worse after embankment indicated by index of 2.55 between 2005-1997 and of
1.84 between 2011-1997. Sediment quality in 2011 was much improved compared to that
in 2005, representing by index of 0.63. Combining water and sediment quality indices
indicated that river quality was not improved; it even became more polluted as values of
river quality index were higher than 1 for all pairs of year comparison (Table 4.7).
82
Table 4.7. Water, sediment, and river quality indices of To Lich River
Pair of comparison (year-year)
Water quality index Sediment quality index River quality index
20111-20052 2.45 0.63 1.54
2005-1997 0.43 2.55 1.49
2011-19973 0.55 1.84 1.19
Heavy metal concentration data: 1 from this study, 2 cited from Kikuchi et al. (2009), 3 cited from HSDC (1997).
4. 4. DISCUSSION
It is clear that water of To Lich River (TLR) should be treated prior to use on crops as the
Mn concentration exceeded recommended level for irrigation (Table 4.4). Since
wastewaters discharged to river reaches between S1 and S3 were mostly of domestic
origin, total load of total organic carbon (TOC) and heavy metal were much lower than
that in downstream reaches between S3 and S5 (Table 4.5). This may suggest the
responsibility of industry for heavy metal discharges rather than of domestic practices.
Higher loads of Cr, Ni, Cu, Zn, and As in river reach between S3-S4 compared to that
between S4-S5 (Table 4.5) indicated that industry within catchment of Lu River, which
joints TLR before sampling site S4, may generate higher amount of those metals
compared to that in Kim Nguu River catchment (Fig.4.1). Load of Cr and Zn in S4-S5
and of As in S2-S3 river reaches were negative (Table 4.5), which must be always ≥ zero.
This may be due to the attenuation rates of this study site are not available, then they were
cited from Ambrose et al. (1991), who indicated dissolved and absorbed capacity of
heavy metal as a function of suspended solid concentrations in streams around the world.
It may suggests that attenuation rate of heavy metals in TLR should be higher as result of
low velocity, higher concentration in water, and others.
Taking into account of TOC, which nearly upped to 4.5 tons/day (Table 4.6) discharged
to Nhue River and of nutrient contents in water (Trinh, 2003), if wastewater is treated
properly and reused in agriculture, it may sustain water supply, reduce input costs, and
increase crop’s productivity and farm income (Rijsberman 2004). An integrated cost-
benefit analysis of wastewater reuse should be conducted, after implementation of an
adequate wastewater treatment system for TLR basin, which is now under consideration.
Currently, agricultural products irrigated using TLR water have been ostracized by
consumers because of water contamination.
83
Sediment of TLR cannot be directly used for any purposes neither agriculture (Steve
1994) nor industry (QCVN 03: 2008/BTNMT; Table 4.2). It must be treated following
suitable guidelines for specific purpose, even treatment and reuse of heavily contaminated
dredged sediments is not a cost-effective alternative to confined disposal (Bert et al.
2009), which becomes secondary source of contamination. Treatment technologies and
experiences have never been put into consideration for sediment of TLR system in Hanoi,
or even in the world for heavy metal contaminated sediment in general (Peng et al. 2009).
This may be the barriers for environmental improvement of TLR. There was a total of
284,000 m3 of sediment in TLR (Table 4.1), which contained high concentration of heavy
metals (Table 4.2). Depending on required quality of sediment after treatment, the
technologies (Foerstner and Apitz 2007) may be different leading to differences in
treatment cost, ranging from 36 to 600 USD/m3 based on composite unit cost estimation
in USA (Myers 2005). Total cost estimated for treating sediment in TLR ranges from 10.2
to 170 million USD, which excludes costs for dredging, transportation, monitoring, and
management of residuals. One again, after treated if it is used for agriculture much benefit
will come to farmers because of high nutrient and organic carbon content in sediment.
Embankment of TLR finished in 2002 (Nguyen 2005), if equalizing sedimentation
deposit annually there was 30,000 m3 of sediment accumulated in TLR bed, it may
require annual cost of 1.2-19 million USD for sediment treatment.
Accumulation of Fe, Mn, Ni, Pb, As, and Cd in sediment was lowest in river reach
between S1 and S2 (Table 4.3), where discharge was mostly from domestic origin (Fig.
4.1). Meanwhile, levels of Cr, Cu, Zn, and TOC was lowest in downstream river reach
between S4 and S5, this may result from higher flow rate of nearly 10 times of
downstream compared to upstream (Table 4.1). The highest accumulations of Mn and As
were also found in downstream river reach (S4-S5; Table 4.3), even their concentrations
in water were not higher than other river reaches (Table 4.4). This is explained by the
higher density of sediment of S4-S5 river reach compared to others in upstream (Table
4.1) and/or those metals prefer to bind with heavier suspended particles. In general,
sediment density increases toward downstream as a result of higher flow rate, which may
bring higher amount of lightly suspended particles. In addition, sediment in further
downstream becomes more compact which restricts re-suspended process to release
heavy metals to water.
Discharge of heavy metals and TOC to Nhue River at the end of TLR in 2011 (Table 4.6)
may be underestimate since it was based on water discharge of only 2 investigated days
84
of March 4 and 5 in dry season in 2011, when there was no rain. The fact is that dirty on
land surface of TLR system basin may contain much organic carbon and heavy metals as
result of transportation, municipal and industrial solid waste disposals, which all will be
discharged to TLR on rainy days. The same case for projected data in 2020, since
concentration of heavy metals and TOC in water are predicted to be the same values in
2011 and uncertainty of population in 2020. Currently, there is no clear plan on building
wastewater treatment plants for whole TLR system basin, which may lead to more serious
water pollution in near future.
Water quality index (WQI) showed that quality of water was much improved after
embankment (Table 4.7) as result of reducing stagnation due to improving flow rate.
Because of no suitable wastewater treatment, river management strategy and/or elevated
discharge of heavy metals to wastewaters from urbanization, water quality has been
becoming worse indicated by increase of WQI to 2.45 between 2011 and 2005 (Table 4.7).
Conversely, it was observed for quality of sediment. Sediment became more polluted
after embankment, indicated by sediment quality index (SQI) of 2.55 and 1.84 for pairs of
2005-1997 and 2011-1997, respectively. The fact is that sediment was almost removed
from river bed as preparation for embankment activities, the new layers of sediment were
accumulated afterward. Since 2002 after completing embankment, population growth,
rapid urbanization, and speed-up of manufacturing activities of industrial zones within
TLR system basin led to increasing the amount and pollution level of discharges, which
contained high amount of suspended particles for sedimentation process (Nguyen 2005).
However comparing between 2005 and 2011, sediment quality was improved (SQI =
0.63). Probably, pre-physical wastewater treatment was paid much attention by industrial
zones to remove as much big particles as possible before discharging as result of issuing
environmental regulations recently. The health of a river should be considered in terms of
both water and sediment bodies, hence river quality index (RQI) was derived from WQI
and SQI (Table 4.7). Quality of TLR has not yet improved since embankment, it even
became worse. To improve quality of a river, wastewater should be treated properly
before discharging to its body. Meanwhile, the main purpose of TLR embankment was
improving water flow rate and reducing solid waste disposal on river banks.
85
4. 5. CONCLUSIONS
This study indicated that concentration of only Mn in water of To Lich River (TLR) inner
Hanoi City, Vietnam exceeds irrigation standard, meanwhile concentrations of Cu, Zn, As,
and Cd in sediment exceed Vietnamese standard for both agricultural and industrial soils.
There is an amount of nearly 300,000 m3 sediments accumulated in TLR since finishing
embankment in 2002, which may cost up to 170 million USD for treatment. Even though,
the technologies and experiences are still limited in study site.
After almost ten years of embankment, quality of TLR was not improved; it even became
more contaminated in terms of heavy metals in both sediment and water. To improve the
environmental quality of a river, embankment is not enough and just an initial stage. In
the next step, wastewater should be fully treated at sources before discharging to TLR and
if possible annual sediment dredging should also be implemented. This not only increases
water flow rate, but also reduces re-suspended process of heavy metals from sediment.
86
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89
CHAPTER 5. GENERAL DISCUSSION AND MANAGEMENT IMPLICATIONS
5.1. GENERAL DISCUSSION
There were many cases of massive fish death in basin of Nhue River reported as results of
discharge of over-polluted wastewaters from To Lich River (TLR), especially in dry
season. Two possibilities of reducing pollution level of wastewater are (1) all wastewater
must be treated following suitable guidelines of different using purpose such as irrigation,
however it may be a long term project since building a system of wastewater treatment
plant for TLR basin with recent amount of 600,000 m3 per day is costly, (2) supplying
unpolluted water from available sources to TLR, which will help reducing pollution to
safety level for both aquaculture and agriculture. As mentioned in Chapter 1, Red river
runs through Hanoi city with huge amount of discharge even in dry season. Currently
water from Red river cannot runs naturally to TLR as result of river encroachment in
upstream, dredging will resolve this problem. Meanwhile, even huge amount of discharge
since water level of Red river in dry season is low which may not runs naturally to TLR, a
pumping station should be established.
Annually, there is about 30,000 m3 sediment accumulated in river bed of TLR as
mentioned in Chapter 4. There are a number of sources leading to high amount of
sediment as: (1) soil erosion from agricultural activities, this has been reduced much as
result of reduce of agricultural land from urbanization in recent years; (2) residuals from
construction activities in TLR basin, which has been much increased as increase of a
number of new buildings, expansion of transportation system, etc.; (3) movement of dust
to city through vehicles, since transportation system surrounding Hanoi has not much
been developed. To reduce amount of sediment in TLR, the cheapest way can be done by
issuing suitable regulations such as all vehicles must be washed before entering the city
and other regulations for construction activities.
Even being highly urbanized in recent decades, there is still an area of agricultural land
which has been directly irrigated by wastewater from TLR through pumping stations
along river and such land still sustains life for a portion of citizens in inner Hanoi city.
The fact is that agricultural products, especially vegetables irrigated by TLR wastewater
have been ostracized by consumers. In the near future, agricultural land may be
destructed as a result of urbanization; establishing irrigation system for such land
becomes cost-inefficient. Therefore, only one way farmers can sustain their products is
90
that they should not only irrigate with wastewater from TLR but also with their own clean
water by suitable ratio, which ensures the quality of products acceptable by government
standard and reduces input cost from using so much clean water and nutrient/fertilizer
that is much available in wastewater.
After embankment in 2002, river banks of TLR have become playgrounds for many
citizens living along and surrounding areas, even it is reported that bad odor is coming
from water body. People may not directly contact with water body, however many water-
borne diseases are originated such as diarrhea from Escherichia coli bacteria, which much
affect human health. E. coli bacteria usually transfers to human through food chain by
consuming raw material such as vegetables which contains E. coli. Those can be avoided
by not eating raw vegetables irrigated by TLR water and/or vegetables should be washed
in a clean manner to remove as much E. coli as possible until safety level. However,
heavy metal accumulation in vegetables cannot be removed by any manners except
reducing wastewater use to minimize metal accumulation. The bad odor may come from
decomposition of many organic materials discharged to TLR from domestic activities,
industry, and hospitals. There is only one way to reduce it is that reducing concentration
of organic carbon in wastewaters through treatment and/or supplying less contaminated
water from Red river to TLR, which was mentioned previously.
Since To Lich is the last river, receiving all wastewaters from inner Hanoi city before
discharging to Nhue River in South Hanoi. To improve quality of TLR, it must be
accompanied with improvement of all sewage system including TLR system of four main
rivers, 25 other small channels, and 518 lakes of different sizes (Fig. 1.1). Management of
small channels and lakes may be difficult, because of illegal disposals of both solid waste
and wastewater from citizens to water bodies, and usually environmental regulations do
not work well in such situation. In addition, sediment accumulated in lakes or small
channels for a long time may contain high level of heavy metals, which has never been
dredged, leading to re-suspend to water body if it is not removed completely.
Besides wastewater treatment to improve quality of water bodies in Hanoi city, dredging
available sediment, which contains high level of heavy metals, is needed. The point was
discussed in Chapter 4 is that the technologies and experiences for treating heavily
contaminated sediments are not available, and it is costly, leading to many difficulties for
situation in Hanoi. Considering disposal of dredged heavily contaminated sediment to
landfill, for a long terms it may become secondary sources of contamination to both
91
surface and underground water. Based on Vietnamese standard, dredged sediment is not
suitable for both industrial and agricultural soils, however if we use with small amount
for an area of agricultural land it may not affect heavy metal accumulation in both soil
and crops, meanwhile crops can use much nutrient and organic carbon available in
sediment to reduce input cost and increase income for farmers. However, this point must
be scientifically confirmed by further research.
Currently, it costs 0.25 USD/person/months for household solid waste in Hanoi, which is
used for management, transportation, and treatment to some extent. The situation for
wastewater is not much considered, because no fee is required for transporting and
especially wastewater treatment plants are not much available in Hanoi. This should be
taken into account as soon as possible by adding cost to volumes of supply water, those
cost will be used for wastewater treatment and indirectly may affect behavior of citizens
on water use to minimize wastewater discharge.
As discussed in detail in Chapter 2 and Chapter 4, source of heavy metal to TLR is
mainly from anthropogenic origin as industry other than domestic activities. The best way
to reduce heavy metal contamination in wastewater is to move industrial zones and/or
much bearing pollution manufacturers out of inner Hanoi city, which not only affect the
environment of water bodies but also on air pollution. Another possibility is management
by environmental regulation to force all manufactures to follow solid waste and
wastewater, and emission standards, which have been less taken care as result of being
rapidly urbanized process. In addition, special taxing on their products for inner city
environmental responsibility may be acceptable. Small industry and handicrafts bring
many benefits to citizens; however it is difficult in term of environmental protection. The
special characteristic of this type of industry in Hanoi city is the scattering distribution, it
is not feasible to collect all wastewater for treatment in centralized treatment plant, while
treatment at source faces a problem of cost-inefficiency.
5.2. PROJECTION OF METAL LOAD
As mentioned previously, population in TLR basin is growing gradually as a result of
natural increase and in-migration; and improved living standard may lead to an increase in
water supply demand from 160 liter/person/day in 2005 to 180 in 2010 and to 200
liter/person/day in 2020 (Nguyen 2005). Assuming the metal concentration in 2020 is
equivalent to value in 2011, the trend for metal load to Nhue River was projected
according to the variation of discharge (Fig 5.1a). The total metal load was also modeled
92
as time progresses (Fig 5.1b). It is the fact that TLR water is not polluted and most under
acceptable concentration following Vietnamese standard for irrigation water. However, the
total metal load increases year by year as result of elevated wastewater discharge. This
amount will be later accumulated in sediment at downstream Nhue River and in a long run
it will much affect water quality and environment there. In 2030, total metal load may
double in 2011 if no suitable action from government is considered urgently (Fig. 5.1b).
Fig. 5.1. Projected metal load discharged to Nhue River at the end of TLR
5.3. MANAGEMENT IMPLICATIONS
Each country has its own heavy metal standard for irrigation water, agriculture soil, safety
environment, etc. In general, developed countries have stricter standards where maximum
permissible metal concentrations are much lower than that in developing countries (Fipps
2003). In addition, number of heavy metal included in a standard is also different.
Developed countries cover a larger number compared to developing countries (MWI
2001). Biologically, a sole metal highly exceeding permissible concentration may not
cause affected, where several metals slightly exceeding permissible concentration may
cause heavily affected (Utsumi and Tsuchiya 2002). To integrate number of heavy metals
and their permissible concentrations together in a standard, representing possible effects
on biota and environment, an integrated standard index (ISI) was proposed and calculated
as following:
(5.1) 1
1∑
=
=n
i i
i
SC
C
nISI
where Ci is concentration of metal i examined in the field, and SCi is standard/permissible
concentration of metal i. The values of ISI were classified into three classes; ISI < 1 (not
y = 266.8 ln(x) - 3390.3R² = 0.97, p = 0.15
0
50
100
150
200
250
300
0 500,000 1,000,000
Met
al lo
ad (k
g da
y-1)
Discharge (m3 day-1)
(a)y = 15986 ln(x) - 121460
R² = 0.90, p = 0.20
0
50
100
150
200
250
300
350
2000 2010 2020 2030
Met
al lo
ad (k
g da
y-1)
Time (year)
(b)
93
affected - permissible), 1 ≤ ISI < 1.5 (affected - conditionally permissible), and ISI ≥ 1.5
(heavily affected - impermissible), which was partly following mean PEC quotients as
indicated by MacDonald et al. (2000) and Long et al. (1998) and details were discussed in
Chapter 3. The applicability of ISI is based on the fact that the appearance of heavy
metals in the field is random if they are from natural source and are dependent when they
are from anthropogenic sources. In process of releasing heavy metal from anthropogenic
sources such as industry, transportation, fertilizing, etc. generally, concentration of heavy
metals examined in the field increases or decreases in parallel. Therefore, increasing ISI
means increasing in concentration of all metals rather than decreasing in concentration of
some metals simultaneously with much increasing that of the others. Similarly to national
standard, the values of ISI classes may also differ country by country. The precise class
intervals of ISI should be examined by biological experiments on metal accumulation in
plants’ organs, consequent effects on their consumers, etc.
An example of calculated ISI in TLR indicated that concentration of five concerned
metals in sediment much exceeded Vietnamese standard for agricultural soil (Table 5.1).
if we consider each metal separately, we may also come to conclusion that sediment from
TLR must not be used for agriculture. It may come to the same conclusion from ISI using
as the values were greater than 2 in all observed years (Table 5.1).
Table 5.1. Heavy metal concentration (mg/kg) in sediment of various sampling years and
integrated standard index (ISI)
Cu Zn As Cd Pb ISI
Sampling in 2011 104.4 547.0 23.1 11.2 76.1 2.69
Sampling in 20051 333.2 390.8 - 9.6 375.3 4.69
Sampling in 19972 158.7 192.7 35.2 - 139.0 2.26
QCVN 03: 2008/BTNMT for agricultural soil3 50 200 12 2 70
1 cited from Nguyen et al. (2010). 2 cited from HSDC (1997). 3 Vietnamese technical regulation on the allowable limits of heavy metals in soils.
Meanwhile, in all seven concerned metals in surface water of TLR (Table 5.2), only Mn
concentration observed in years 1997 and 2011 slightly exceeded WHO irrigation water
guidelines, strictly based on guidelines we may conclude that wastewater from TLR
cannot be used for irrigation. However, using ISI leads to conclusion that it can be used
94
since ISI values are much lower than 1, which may again enlarge usage capability of
wastewater for irrigation in the shortage of water resources.
Table 5.2. Heavy metal concentration (µg/L) in water of various sampling years and
integrated standard index (ISI)
Cr Mn Ni Cu Zn As Pb ISI
Sampling in 2011 2.6 220.9 6.8 4.6 44.4 40.6 7.8 0.23
Sampling in 20051 8.4 114.0 6.0 4.6 31.6 5.6 1.9 0.11
Sampling in 19972 13.0 220.0 4.0 20.0 2,000 66.0 160.0 0.43
Irrigation water guidelines3
100 200 200 200 2,000 100 5,000
1 cited from Kikuchi et al. (2009). 2 cited from HSDC (1997). 3 WHO (2006).
Except Mn contents in samples of 1997 and 2011, concentrations of other metals in
surface water of TLR were still under Vietnamese permissible limit for irrigation water
(Table 5.2). As stated in Chapter 1, there are five industrial zones of nearly 100 factories
discharging untreated and/or partly treated wastewater to TLR basin. Obviously, many of
100 mentioned factories have been discharging polluted wastewater to TLR system
(Nguyen 2005), which is then diluted with other un- or less polluted water sources such as
domestic sewage, storm water, agriculture etc. resulting in unpolluted surface water at the
end of TLR (Table 5.2). On the other hand, industrial zones or factories may not treat
their wastewater; instead they lower concentration by dilution for the purpose of
compliance with effluent discharge standard. A stricter standard for heavy metals may be
required for study site so called “Total Pollutant Load Control Standard” - TPLCS, which
has been applied in developed countries for COD, nitrogen, and phosphorus (JMoE 2011;
Moon 2005).
TPLCS (kg/day) has been set as a permissible limit of pollutant discharge load contained
in effluents per day for each business establishment in basin and is calculated as Eq. 5.2.
(5.3) 10
e therefor(5.2), 10**3
3
Q*
TPLCS CQCTPLCS ==
where, C is metal concentration in wastewater (mg/L) and Q is wastewater quantity
(m3/day).
95
General speaking, Q value increases year by year (Table 4.6; 5.3) as result of population
growth, freshwater demand increase, and industrial development. Therefore, all business
establishments must improve effluent discharge quality/reduce metal concentration in
their wastewater through upgrading wastewater treatment facilities and safe operation to
comply with TPLCS.
Japanese Ministry of Environment (JMoE 2011) proposed a formula for establishing
TPLCS in Japan as following Eq. 5.4.
310*)***( jjiioo QCQCQCTPLCS ++= (5.4)
where, C and Q are concentration and discharge (m3/day) of the effluent, respectively.
Co*Qo applied to water volume before July 1, 1980. Ci*Q i applied to water volume which
increased between July 1, 1980 and June 30, 1991. Cj*Q j applied to water volume which
increased after July 1, 1991. Three mentioned period divisions were taken in accordance
with the time of construction and expansion of production facilities in Japan.
As a developed country, the quantity of specified effluent is the value declared by
factories and business establishments (In Japan, operators must notify officials about the
volume and quality of effluent and wastewater treatment method when constructing a new
production facility or expanding an existing one). Therefore, the establishment of TPLCS
for any areas becomes easy because of availability of previous data on volume and quality
of its effluent.
Conversely, in a developing country and being urbanized city like Hanoi, where this
study was carried out, many technologies in five industrial zones were established in
1950s and the data on volume and quality of effluent from these industrial zones for the
period divisions in accordance with the time of construction and expansion of production
were not available. Therefore, a simple formula to estimate TPLCS for TLR in year 2020
(Table 5.3) is proposed as Eq. 5.5.
202020202020
* QCTPLCSin in in
= (5.5)
where, C in 2020 is the value taken from current standards and guideline for water quality
(Table 5.3) and Q in 2020 is discharge in 2020 as mentioned earlier (Table 4.6). As stated in
details, water of TLR has been being used for irrigating agriculture land and since the
river runs through dense residential areas with a population of around 2 million people.
96
Therefore two standards (Vietnamese standard for surface water used for domestic water
supply (TCVN 5942-1995, column A) and Vietnamese technical regulation on Water
Quality for irrigated agriculture (QCVN 39: 2011/BTNMT) and one guideline (mean
concentration of freshwater in the world) were used for three scenarios, which local
government may consider achieving water quality of TLR basin in 2020.
Quotient (Table 5.4) was estimated as Eq. 5.6.
2011in or 2005in
2020in
load Surveyed
load ingCorrespond (times)Quotient = (5.6)
Table 5.3. Selected values for heavy metal concentration, corresponding load in 2020, and
surveyed load in 2005 and in 2011.
Cr Mn Ni Cu Zn As Pb
Selected values for metal concentration ( µg/L) Mean freshwater in the world1 1 8 0.5 3 15 0.5 3
TCVN 5942-1995 A, surface water for domestic water supply2
100 100 100 100 1000 50 50
QCVN 39: 2011/BTNMT, water quality for irrigation3 100 - - 500 2000 50 50
Corresponding load (kg/day) - TPLCS in 2020 Mean freshwater in the world 0.72 5.75 0.36 2.16 10.78 0.36 2.16
TCVN 5942-1995 A, surface water for domestic water supply
71.88 71.88 71.88 71.88 718.75 35.94 35.94
QCVN 39: 2011/BTNMT, water quality for irrigation
71.88 - - 359.38 1437.50 35.94 35.94
Surveyed load (kg/day)
In 2005 3.79 51.41 2.71 2.07 14.25 2.53 0.86
In 2011 1.15 116.00 4.04 2.31 16.17 16.22 5.77
1 Median values of freshwater in the world (Bowen 1979). 2 Vietnamese standard for surface water used for domestic water supply with appropriate treatment. 3 Vietnamese technical regulation on water quality for irrigated agriculture.
To achieve the first scenario, metal concentrations in water of TLR are under mean
concentrations of freshwater in the world, local government must take more actions to
97
reduce metal load in 2020 for example (Table 5.3) 81% for Cr, 95% for Mn, 91% for Ni,
and 7%, 33%, 98%, 63% for Cu, Zn, As and Pb, respectively, if we adopt the severer
necessary reduction according to the surveyed load in 2005 or 2011. In achieving such
figures, not only currently or newly business establishments, but also the oldest
technology ones, which were established in 1950s must also improve their production
technology and update advanced wastewater treatment technology. This scenario may be
infeasible for Hanoi City to achieve in 2020, since it is being urbanized and in stage of
limited budget for environmental improvement, compared to others more urgent goals
such as promoting economic growth.
In the second scenario, achieving TCVN 5942-1995, column A applied for surface water
using for source of domestic with appropriate treatment, the local government must also
take actions to reduce metal load of Mn to 38% (Table 5.4) and to maintain the load
increase of other metals under acceptable quotients as indicated in Table 5.4. This
scenario is more feasible compared to the first one as mentioned previously. To achieve
this probably only old business establishments establishing in 1950s with outdated
technology are the target for increasing quality of their effluents. Local government may
take regular environmental monitoring and inspection to them, supporting them finance in
improving technology or in moving out of inner city.
For the last scenario, water quality of TLR must achieve Vietnamese irrigation water
standard (QCVN 39: 2011/BTNMT), this is the most feasible scenario in three mentioned.
The local government only needs to keep actions, which are being applied to ensure that
increase of metal load under acceptable quotients (Table 5.4). For business establishments,
they may not need to improve their production technology and change wastewater
treatment technology, however they need to control their effluent quantity as current
volume. In case, there are any change in effluent quantity they must inform local
government for any actions if necessary to ensure the quotient of total load under
acceptability.
As stated, the availability of data on quality and quality of effluent of different business
establishments in TLR basin are not available. However, toward a friendly environment
local government must take actions then such data will be available soon in near future,
which may include compositions of effluent of different sources such as industry,
domestic sewage, etc. Therefore, practical standard value of metal concentrations will be
specifically set according to ratio between household and industrial discharge, type of
98
business establishment in basin of TLR, and the age of applied technologies, which has
been widely carried out in developed countries currently.
Table 5.4. Increasing and reducing quotient (times) of metal load in 2020 to that in 2005
and in 2011
Cr Mn Ni Cu Zn As Pb
Mean freshwater in the world
2005 -0.81 -0.89 -0.87 1.04 -0.24 -0.86 2.52
2011 -0.38 -0.95 -0.91 -0.07 -0.33 -0.98 -0.63
TCVN 5942-1995 A, surface water for domestic water supply
2005 18.98 1.40 26.57 34.65 50.44 14.23 41.95
2011 62.24 -0.38 17.78 31.12 44.46 2.21 6.22
QCVN 39: 2011/BTNMT, water quality for irrigation
2005 18.98
173.26 100.88 14.23 41.95
2011 62.24
155.60 88.91 2.21 6.22
Negative values mean reduction.
The ISI values (Table 5.5) may also indicate the management schemes for local
government. Any management scheme is aiming at reducing ISI value to acceptable
figure as smaller than 1 as discussed previously. ISI value of the first scenario (mean
concentration of freshwater in the world) is 14.8, nearly 15 times of acceptable value.
Therefore, much more actions from local government must be carried out. Meanwhile, for
the second scenario (TCVN 5942-1995 A for supplying clean water after suitable
treatment) fewer actions are required because of lower value of ISI (0.4) as the same
discussed in the values of quotient previously. Finally, for the third scenario representing
by lowest value of ISI (0.2), no new actions may need to take into account.
Table 5.5. Integrated Standard Index (ISI) of different scenarios
Scenario on water quality achieved in 2020 Current value of ISI1
Mean freshwater in the world 14.8
TCVN 5942-1995 A for supplying clean water after suitable treatment
0.4
QCVN 39: 2011/BTNMT, irrigation 0.2
1 ISI was calculated as Eq. 5. 1.
99
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1. UNESCO and EOLSS.
WHO (2006) Guidelines for the safe use of wastewater, excreta and greywater: Volume
II: Wastewater Use in Agriculture.
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CHAPTER 6. CONCLUSIONS AND RECOMMENDATIONS
Heavy metal assessment and source discrimination are important for environmental
improvement and protection strategy, especially for urbanizing cities as Hanoi, Vietnam.
The concentrations of Mn, Fe, Ni, Cr, Cu, Pb, Zn, As, and Cd were determined to
evaluate the level of contamination of To Lich River (TLR) in Hanoi city. All metal
concentrations in 0-10 cm water samples, except Mn, were lower than the maximum
permitted concentration for irrigation water standard. Meanwhile, concentrations of As,
Cd and Zn in 0-30 cm sediments were likely to have adverse effects on agriculture and
aquatic life. The sediment was not polluted with Cr, Mn, Fe and Ni, and then pollution
level increased in order of Cu < Pb < Zn < As < Cd. As and Mn in sediment were derived
from both lithogenic and anthropogenic sources, while Cu, Pb, Zn, Cr, Cd, and Ni
originated from anthropogenic sources such as vehicular fumes for Pb and metallic
discharge from industrial sources and fertilizer application for other metals. It is
concluded that environment of To Lich River has not yet been improved even several
regulations on environmental protection had been issued recently.
In nine sampling position along TLR, Cd was the most contaminated metal causing heavy
sediment contamination for six sampling positions. Sediments at all sites exceeded
maximum permissible concentrations of potentially toxic heavy metal for crops and were
considered to be toxic for aquatic life. Cluster analysis demonstrated that the sediment
from TLR can be significantly distinguished into three groups in terms of contamination
degrees. Accumulation ability of heavy metals in sediment was in order of Cr > Cu > Ni
> Zn > Pb > As > Mn based on accumulation coefficient.
To improve quality of TLR, the embankment was carried out in 1998 and finished in
2002. The results indicated that currently there is about 284,000 m3 sediment accumulated
in TLR bed, which is under high contamination of Cr, Mn, Fe, Ni Cu, Zn, As, Cd, and Pb
with a total of 7,347 tons of all concerned metals. It may cost up to 170 million USD for
treatment. Even though, the technologies and experiences are still limited in study site.
Domestic-discharged river reaches received much lower metal loads, roughly 8-28%
compared to river reaches of both domestic and industrial inputs. Total load of all nine
concerned metals at the end of TLR is 161.7 kg/day, which is finally discharged to Nhue
River at South Hanoi. Water quality was improved much right after finishing
embankment, then it gradually deteriorated. Meanwhile, sediment quality became even
much worse after embankment. Relative river quality index as equal weight for both
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water and sediment quality indices indicated that quality of TLR was not much improved
after the embankment. It even became worse due to the urbanization in recent years. To
improve the environmental quality of a river, embankment is not enough and just an
initial stage. In the next step, wastewater should be fully treated at sources before
discharging to TLR and if possible annual sediment dredging should also be implemented.
This not only increases water flow rate, but also reduces re-suspended process of heavy
metals from sediment.
Integrated standard index, representing both number of heavy metals and their
permissible concentration, should be further considered and encouraged in action for
agricultural and environmental standards in the reality of shortage of resource for
irrigation water and plants’ nutrition. Otherwise, the use of such resources will be banned
even concentration of a sole metal slightly exceeds permissible limit.
Three scenarios on Total Pollutant Load Control Standard (TPLCS) for TLR basin were
proposed, at which local government may base on to manage the basin toward friendly
environment according to their capabilities. The further studies on this topic for
establishing practical TPLCS and standard value of metal concentrations for industrial
and domestic discharge, business establishments, different types of industry, etc. must be
carried out to comply with stricter environmental standard as result of improvement of
living standard in near future.
To Lich River is the main river in To Lich River system, which receives untreated
wastewater from industry and domestic activities in inner city Hanoi. The deterioration of
river quality has caused adverse effects on surrounding environment, and may pose
potential threat to human health. In order to improve water quality management, it is
necessary to strengthen the monitoring system of water environment with an increase of
monitoring points, monitoring frequency and parameters; and a better quality assurance
and quality control. In addition, the database should be easily access for publicity, which
benefits not only local government but also citizens. These monitoring and information
solutions may contribute to a more effective management of quality of To Lich River and
all water bodies in Hanoi city in general.
